Split (1)

train · 300k rows

paper_url stringlengths 36 81	paper_title stringlengths 1 242 ⌀	paper_arxiv_id stringlengths 9 16 ⌀	paper_url_abs stringlengths 18 314	paper_url_pdf stringlengths 21 935 ⌀	repo_url stringlengths 26 200	is_official bool 2 classes	mentioned_in_paper bool 2 classes	mentioned_in_github bool 2 classes	framework stringclasses 9 values
https://paperswithcode.com/paper/wide-inference-network-for-image-denoising	Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior	1707.05414	http://arxiv.org/abs/1707.05414v5	http://arxiv.org/pdf/1707.05414v5.pdf	https://github.com/shibuiwilliam/DeepLearningDenoise	false	false	true	none
https://paperswithcode.com/paper/stability-of-periodic-orbits-in-no-slip	Stability of periodic orbits in no-slip billiards	1612.03355	http://arxiv.org/abs/1612.03355v1	http://arxiv.org/pdf/1612.03355v1.pdf	https://github.com/drscook/no_slip_billiards	false	false	true	none
https://paperswithcode.com/paper/beyond-a-gaussian-denoiser-residual-learning	Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising	1608.03981	http://arxiv.org/abs/1608.03981v1	http://arxiv.org/pdf/1608.03981v1.pdf	https://github.com/shibuiwilliam/DeepLearningDenoise	false	false	true	none
https://paperswithcode.com/paper/graph-attention-networks	Graph Attention Networks	1710.10903	http://arxiv.org/abs/1710.10903v3	http://arxiv.org/pdf/1710.10903v3.pdf	https://github.com/YunseobShin/wiki_GAT	false	false	true	tf
https://paperswithcode.com/paper/dynamic-word-embeddings	Dynamic Word Embeddings	1702.08359	http://arxiv.org/abs/1702.08359v2	http://arxiv.org/pdf/1702.08359v2.pdf	https://github.com/accessai/dynamic_word_embeddings	false	false	true	pytorch
https://paperswithcode.com/paper/learning-2d-3d-correspondences-to-solve-the	Learning 2D-3D Correspondences To Solve The Blind Perspective-n-Point Problem	2003.06752	https://arxiv.org/abs/2003.06752v1	https://arxiv.org/pdf/2003.06752v1.pdf	https://github.com/Liumouliu/Deep_blind_PnP	true	true	true	pytorch
https://paperswithcode.com/paper/hardware-distortion-correlation-has	Hardware Distortion Correlation Has Negligible Impact on UL Massive MIMO Spectral Efficiency	1811.02007	https://arxiv.org/abs/1811.02007v2	https://arxiv.org/pdf/1811.02007v2.pdf	https://github.com/emilbjornson/distortion-correlation	true	true	true	none
https://paperswithcode.com/paper/a-collective-knowledge-workflow-for	A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques	1801.08024	http://arxiv.org/abs/1801.08024v1	http://arxiv.org/pdf/1801.08024v1.pdf	https://github.com/ctuning/ck-rpi-optimization-results	true	true	true	none
https://paperswithcode.com/paper/dtw-at-qur-an-qa-2022-utilising-transfer	DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain	2205.06025	https://arxiv.org/abs/2205.06025v1	https://arxiv.org/pdf/2205.06025v1.pdf	https://github.com/damithdr/questionanswering	true	true	false	pytorch
https://paperswithcode.com/paper/deep-residual-learning-for-image-recognition	Deep Residual Learning for Image Recognition	1512.03385	http://arxiv.org/abs/1512.03385v1	http://arxiv.org/pdf/1512.03385v1.pdf	https://github.com/gcr/torch-residual-networks	false	false	true	torch
https://paperswithcode.com/paper/mobilenets-efficient-convolutional-neural	MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications	1704.04861	http://arxiv.org/abs/1704.04861v1	http://arxiv.org/pdf/1704.04861v1.pdf	https://github.com/Edmonton-School-of-AI/ml5-Simple-Image-Classification	false	false	true	none
https://paperswithcode.com/paper/conditional-independence-testing-based-on-a	Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information	1709.01447	http://arxiv.org/abs/1709.01447v1	http://arxiv.org/pdf/1709.01447v1.pdf	https://github.com/jakobrunge/tigramite	true	true	false	pytorch
https://paperswithcode.com/paper/root-mean-square-layer-normalization	Root Mean Square Layer Normalization	1910.07467	https://arxiv.org/abs/1910.07467v1	https://arxiv.org/pdf/1910.07467v1.pdf	https://github.com/bzhangGo/rmsnorm	true	true	false	pytorch
https://paperswithcode.com/paper/effective-approaches-to-attention-based	Effective Approaches to Attention-based Neural Machine Translation	1508.04025	http://arxiv.org/abs/1508.04025v5	http://arxiv.org/pdf/1508.04025v5.pdf	https://github.com/b-etienne/Seq2seq-PyTorch	false	false	true	pytorch
https://paperswithcode.com/paper/neural-machine-translation-by-jointly	Neural Machine Translation by Jointly Learning to Align and Translate	1409.0473	http://arxiv.org/abs/1409.0473v7	http://arxiv.org/pdf/1409.0473v7.pdf	https://github.com/b-etienne/Seq2seq-PyTorch	false	false	true	pytorch
https://paperswithcode.com/paper/parameter-free-spatial-attention-network-for	Parameter-Free Spatial Attention Network for Person Re-Identification	1811.12150	http://arxiv.org/abs/1811.12150v1	http://arxiv.org/pdf/1811.12150v1.pdf	https://github.com/HRanWang/Spatial-Attention	false	false	true	pytorch
https://paperswithcode.com/paper/generalized-robust-bayesian-committee-machine	Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression	1806.00720	http://arxiv.org/abs/1806.00720v1	http://arxiv.org/pdf/1806.00720v1.pdf	https://github.com/LiuHaiTao01/GRBCM	true	true	true	none
https://paperswithcode.com/paper/near-optimal-edge-evaluation-in-explicit	Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs	1706.09351	http://arxiv.org/abs/1706.09351v1	http://arxiv.org/pdf/1706.09351v1.pdf	https://github.com/sanjibac/matlab_learning_collision_checking	false	false	true	none
https://paperswithcode.com/paper/ivd-net-intervertebral-disc-localization-and	IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet	1811.08305	http://arxiv.org/abs/1811.08305v1	http://arxiv.org/pdf/1811.08305v1.pdf	https://github.com/josedolz/IVD-Net	false	false	true	pytorch
https://paperswithcode.com/paper/a-neural-representation-of-sketch-drawings	A Neural Representation of Sketch Drawings	1704.03477	http://arxiv.org/abs/1704.03477v4	http://arxiv.org/pdf/1704.03477v4.pdf	https://github.com/thinkingmachines/christmAIs	false	false	true	tf
https://paperswithcode.com/paper/end-to-end-sequence-labeling-via-bi	End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF	1603.01354	http://arxiv.org/abs/1603.01354v5	http://arxiv.org/pdf/1603.01354v5.pdf	https://github.com/XiafeiYu/CNN_BILSTM_CRF	false	false	true	tf
https://paperswithcode.com/paper/learning-deep-features-for-discriminative	Learning Deep Features for Discriminative Localization	1512.04150	http://arxiv.org/abs/1512.04150v1	http://arxiv.org/pdf/1512.04150v1.pdf	https://github.com/HRanWang/Spatial-Attention	false	false	true	pytorch
https://paperswithcode.com/paper/optimizing-statistical-machine-translation	Optimizing Statistical Machine Translation for Text Simplification	null	https://aclanthology.org/Q16-1029	https://aclanthology.org/Q16-1029.pdf	https://github.com/cocoxu/simplification	true	true	false	none
https://paperswithcode.com/paper/eidos-indra-delphi-from-free-text-to	Eidos, INDRA, \& Delphi: From Free Text to Executable Causal Models	null	https://aclanthology.org/N19-4008	https://aclanthology.org/N19-4008.pdf	https://github.com/ml4ai/delphi	true	true	false	none
https://paperswithcode.com/paper/detecting-traffic-lights-by-single-shot	Detecting Traffic Lights by Single Shot Detection	1805.02523	http://arxiv.org/abs/1805.02523v3	http://arxiv.org/pdf/1805.02523v3.pdf	https://github.com/julimueller/tl_ssd	true	true	false	none
https://paperswithcode.com/paper/melody-generation-for-pop-music-via-word	Melody Generation for Pop Music via Word Representation of Musical Properties	1710.11549	http://arxiv.org/abs/1710.11549v1	http://arxiv.org/pdf/1710.11549v1.pdf	https://github.com/mil-tokyo/NeuralMelody	true	true	true	none
https://paperswithcode.com/paper/active-learning-amidst-logical-knowledge	Active Learning amidst Logical Knowledge	1709.08850	http://arxiv.org/abs/1709.08850v1	http://arxiv.org/pdf/1709.08850v1.pdf	https://github.com/eaplatanios/makina	true	true	false	none
https://paperswithcode.com/paper/bpr-bayesian-personalized-ranking-from	BPR: Bayesian Personalized Ranking from Implicit Feedback	1205.2618	http://arxiv.org/abs/1205.2618v1	http://arxiv.org/pdf/1205.2618v1.pdf	https://github.com/massquantity/LibRecommender	false	false	false	tf
https://paperswithcode.com/paper/on-device-neural-language-model-based-word	On-Device Neural Language Model Based Word Prediction	null	https://aclanthology.org/C18-2028	https://aclanthology.org/C18-2028.pdf	https://github.com/meinwerk/WordPrediction	true	true	false	none
https://paperswithcode.com/paper/see-more-know-more-unsupervised-video-object-1	See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks	2001.06810	https://arxiv.org/abs/2001.06810v1	https://arxiv.org/pdf/2001.06810v1.pdf	https://github.com/carrierlxk/COSNet	true	true	false	pytorch
https://paperswithcode.com/paper/colorization-as-a-proxy-task-for-visual	Colorization as a Proxy Task for Visual Understanding	1703.04044	http://arxiv.org/abs/1703.04044v3	http://arxiv.org/pdf/1703.04044v3.pdf	https://github.com/gustavla/self-supervision	true	true	true	tf
https://paperswithcode.com/paper/named-entity-recognition-for-hindi-english	Named Entity Recognition for Hindi-English Code-Mixed Social Media Text	null	https://aclanthology.org/W18-2405	https://aclanthology.org/W18-2405.pdf	https://github.com/SilentFlame/Named-Entity-Recognition	true	true	false	none
https://paperswithcode.com/paper/gradient-harmonized-single-stage-detector	Gradient Harmonized Single-stage Detector	1811.05181	http://arxiv.org/abs/1811.05181v1	http://arxiv.org/pdf/1811.05181v1.pdf	https://github.com/xialuxi/GHMLoss-caffe	false	false	true	none
https://paperswithcode.com/paper/injecting-relational-structural	Injecting Relational Structural Representation in Neural Networks for Question Similarity	1806.08009	http://arxiv.org/abs/1806.08009v1	http://arxiv.org/pdf/1806.08009v1.pdf	https://github.com/aseveryn/deep-qa	true	true	false	none
https://paperswithcode.com/paper/sgdlibrary-a-matlab-library-for-stochastic	SGDLibrary: A MATLAB library for stochastic gradient descent algorithms	1710.10951	http://arxiv.org/abs/1710.10951v2	http://arxiv.org/pdf/1710.10951v2.pdf	https://github.com/hiroyuki-kasai/SGDLibrary	true	true	true	none
https://paperswithcode.com/paper/stochastic-primal-dual-hybrid-gradient	Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications	1706.04957	http://arxiv.org/abs/1706.04957v2	http://arxiv.org/pdf/1706.04957v2.pdf	https://github.com/mehrhardt/spdhg	false	false	true	none
https://paperswithcode.com/paper/adaptive-path-integral-autoencoder	Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems	1807.02128	http://arxiv.org/abs/1807.02128v4	http://arxiv.org/pdf/1807.02128v4.pdf	https://github.com/yjparkLiCS/18-NIPS-APIAE	true	true	true	tf
https://paperswithcode.com/paper/pointnet-deep-learning-on-point-sets-for-3d	PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation	1612.00593	http://arxiv.org/abs/1612.00593v2	http://arxiv.org/pdf/1612.00593v2.pdf	https://github.com/YanWei123/PointNet-encoder-and-FoldingNet-decoder-add-quantization-change-latent-code-size-from-512-to-1024	false	false	true	pytorch
https://paperswithcode.com/paper/self-distribution-binary-neural-networks	Self-Distribution Binary Neural Networks	2103.02394	https://arxiv.org/abs/2103.02394v2	https://arxiv.org/pdf/2103.02394v2.pdf	https://github.com/pingxue-hfut/sd-bnn	true	true	false	pytorch
https://paperswithcode.com/paper/neural-reprojection-error-merging-feature	Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation	2103.07153	https://arxiv.org/abs/2103.07153v1	https://arxiv.org/pdf/2103.07153v1.pdf	https://github.com/germain-hug/NRE	false	false	true	pytorch
https://paperswithcode.com/paper/gl2vec-graph-embedding-enriched-by-line	GL2vec: Graph Embedding Enriched by Line Graphs with Edge Features	null	https://link.springer.com/chapter/10.1007/978-3-030-36718-3_1	https://link.springer.com/chapter/10.1007/978-3-030-36718-3_1	https://github.com/benedekrozemberczki/karateclub	false	false	false	none
https://paperswithcode.com/paper/high-frequency-instabilities-of-stokes-waves	High-Frequency Instabilities of Stokes Waves	2107.11489	https://arxiv.org/abs/2107.11489v1	https://arxiv.org/pdf/2107.11489v1.pdf	https://github.com/rpac5130/wwp_isola	true	false	false	none
https://paperswithcode.com/paper/a-hierarchical-neural-attention-based-text	A Hierarchical Neural Attention-based Text Classifier	null	https://aclanthology.org/D18-1094	https://aclanthology.org/D18-1094.pdf	https://github.com/koustuvsinha/hier-class	true	true	false	pytorch
https://paperswithcode.com/paper/stacked-filters-stationary-flow-for-hardware	Stacked Filters Stationary Flow For Hardware-Oriented Acceleration Of Deep Convolutional Neural Networks	1801.07459	http://arxiv.org/abs/1801.07459v3	http://arxiv.org/pdf/1801.07459v3.pdf	https://github.com/songhan/Deep-Compression-AlexNet	true	true	false	caffe2
https://paperswithcode.com/paper/spectral-normalisation-for-deep-reinforcement	Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective	2105.05246	https://arxiv.org/abs/2105.05246v1	https://arxiv.org/pdf/2105.05246v1.pdf	https://github.com/floringogianu/snrl	true	true	false	pytorch
https://paperswithcode.com/paper/a-generative-joint-additive-sequential-model	A Generative Joint, Additive, Sequential Model of Topics and Speech Acts in Patient-Doctor Communication	null	https://aclanthology.org/D13-1182	https://aclanthology.org/D13-1182.pdf	https://github.com/bwallace/JAS	true	true	false	none
https://paperswithcode.com/paper/decoding-supercodes-of-gabidulin-codes-and	Decoding supercodes of Gabidulin codes and applications to cryptanalysis	2103.02700	https://arxiv.org/abs/2103.02700v3	https://arxiv.org/pdf/2103.02700v3.pdf	https://github.com/mbombar/Attack_on_LIGA	true	true	false	none
https://paperswithcode.com/paper/exploring-transfer-learning-for-low-resource	Exploring Transfer Learning for Low Resource Emotional TTS	1901.04276	http://arxiv.org/abs/1901.04276v1	http://arxiv.org/pdf/1901.04276v1.pdf	https://github.com/SeanPLeary/dc_tts-transfer-learning	false	false	false	tf
https://paperswithcode.com/paper/detecting-adversarial-samples-from-artifacts	Detecting Adversarial Samples from Artifacts	1703.00410	http://arxiv.org/abs/1703.00410v3	http://arxiv.org/pdf/1703.00410v3.pdf	https://github.com/rfeinman/detecting-adversarial-samples	true	true	true	tf
https://paperswithcode.com/paper/long-term-temporal-convolutions-for-action	Long-term Temporal Convolutions for Action Recognition	1604.04494	http://arxiv.org/abs/1604.04494v2	http://arxiv.org/pdf/1604.04494v2.pdf	https://github.com/gulvarol/ltc	false	false	true	torch
https://paperswithcode.com/paper/bayesian-cosmic-density-field-inference-from	Bayesian cosmic density field inference from redshift space dark matter maps	1810.05189	http://arxiv.org/abs/1810.05189v2	http://arxiv.org/pdf/1810.05189v2.pdf	https://github.com/egpbos/barcode	true	true	true	none
https://paperswithcode.com/paper/generating-adversarial-computer-programs-1	Generating Adversarial Computer Programs using Optimized Obfuscations	2103.11882	https://arxiv.org/abs/2103.11882v1	https://arxiv.org/pdf/2103.11882v1.pdf	https://github.com/ALFA-group/adversarial-code-generation	true	true	false	pytorch
https://paperswithcode.com/paper/auto-encoding-variational-bayes	Auto-Encoding Variational Bayes	1312.6114	http://arxiv.org/abs/1312.6114v10	http://arxiv.org/pdf/1312.6114v10.pdf	https://github.com/lyeoni/pytorch-mnist-VAE	false	false	true	pytorch
https://paperswithcode.com/paper/is-there-a-black-hole-in-the-center-of-the	Is there a black hole in the center of the Sun?	2312.07647	https://arxiv.org/abs/2312.07647v2	https://arxiv.org/pdf/2312.07647v2.pdf	https://github.com/earlbellinger/black-hole-sun	true	true	false	none
https://paperswithcode.com/paper/training-machine-learning-models-by	Training Machine Learning Models by Regularizing their Explanations	1810.00869	http://arxiv.org/abs/1810.00869v1	http://arxiv.org/pdf/1810.00869v1.pdf	https://github.com/dtak/rrr	true	true	false	none
https://paperswithcode.com/paper/infogan-interpretable-representation-learning	InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets	1606.03657	http://arxiv.org/abs/1606.03657v1	http://arxiv.org/pdf/1606.03657v1.pdf	https://github.com/VitoRazor/Gan_Architecture	false	false	true	tf
https://paperswithcode.com/paper/generative-adversarial-networks	Generative Adversarial Networks	1406.2661	https://arxiv.org/abs/1406.2661v1	https://arxiv.org/pdf/1406.2661v1.pdf	https://github.com/singhsidhukuldeep/Generative-Adversarial-Network-GAN	false	false	true	none
https://paperswithcode.com/paper/structure-aware-convolutional-neural-networks	Structure-Aware Convolutional Neural Networks	null	http://papers.nips.cc/paper/7287-structure-aware-convolutional-neural-networks	http://papers.nips.cc/paper/7287-structure-aware-convolutional-neural-networks.pdf	https://github.com/vector-1127/SACNNs	true	true	false	tf
https://paperswithcode.com/paper/verifying-strong-eventual-consistency-in	Verifying Strong Eventual Consistency in Distributed Systems	1707.01747	http://arxiv.org/abs/1707.01747v3	http://arxiv.org/pdf/1707.01747v3.pdf	https://github.com/octalsrc/octar	false	false	true	none
https://paperswithcode.com/paper/hierarchical-probabilistic-model-for-blind	Hierarchical Probabilistic Model for Blind Source Separation via Legendre Transformation	1909.11294	https://arxiv.org/abs/1909.11294v3	https://arxiv.org/pdf/1909.11294v3.pdf	https://github.com/sjmluo/IGLLM	true	true	true	none
https://paperswithcode.com/paper/a-systematic-dnn-weight-pruning-framework	A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers	1804.03294	http://arxiv.org/abs/1804.03294v3	http://arxiv.org/pdf/1804.03294v3.pdf	https://github.com/KaiqiZhang/caffe-admm	false	false	true	none
https://paperswithcode.com/paper/disentangling-factors-of-variation-with-cycle	Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders	1804.10469	http://arxiv.org/abs/1804.10469v1	http://arxiv.org/pdf/1804.10469v1.pdf	https://github.com/ananyahjha93/challenges-in-disentangling	false	false	true	pytorch
https://paperswithcode.com/paper/learning-for-video-super-resolution-through	Learning for Video Super-Resolution through HR Optical Flow Estimation	1809.08573	http://arxiv.org/abs/1809.08573v2	http://arxiv.org/pdf/1809.08573v2.pdf	https://github.com/LongguangWang/SOF-VSR	false	false	true	pytorch
https://paperswithcode.com/paper/180809781	Self-Attentive Sequential Recommendation	1808.09781	http://arxiv.org/abs/1808.09781v1	http://arxiv.org/pdf/1808.09781v1.pdf	https://github.com/kang205/SASRec	false	false	false	tf
https://paperswithcode.com/paper/drit-diverse-image-to-image-translation-via	DRIT++: Diverse Image-to-Image Translation via Disentangled Representations	1905.01270	https://arxiv.org/abs/1905.01270v2	https://arxiv.org/pdf/1905.01270v2.pdf	https://github.com/taki0112/DRIT-Tensorflow	false	false	false	tf
https://paperswithcode.com/paper/shape-robust-text-detection-with-progressive	Shape Robust Text Detection with Progressive Scale Expansion Network	1806.02559	http://arxiv.org/abs/1806.02559v1	http://arxiv.org/pdf/1806.02559v1.pdf	https://github.com/liuheng92/tensorflow_PSENet	false	false	true	tf
https://paperswithcode.com/paper/bayesian-cosmic-web-reconstruction-barcode	Bayesian Cosmic Web Reconstruction: BARCODE for Clusters	1611.01220	http://arxiv.org/abs/1611.01220v1	http://arxiv.org/pdf/1611.01220v1.pdf	https://github.com/egpbos/barcode	false	false	true	none
https://paperswithcode.com/paper/textsnake-a-flexible-representation-for	TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes	1807.01544	https://arxiv.org/abs/1807.01544v2	https://arxiv.org/pdf/1807.01544v2.pdf	https://github.com/princewang1994/TextSnake.pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/robust-estimation-and-generative-adversarial	Robust Estimation and Generative Adversarial Nets	1810.02030	http://arxiv.org/abs/1810.02030v3	http://arxiv.org/pdf/1810.02030v3.pdf	https://github.com/zhuwzh/Robust-GAN-Center	true	true	true	pytorch
https://paperswithcode.com/paper/the-unreasonable-effectiveness-of-noisy-data	The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition	1511.06789	http://arxiv.org/abs/1511.06789v3	http://arxiv.org/pdf/1511.06789v3.pdf	https://github.com/google/goldfinch	true	true	true	none
https://paperswithcode.com/paper/tags2parts-discovering-semantic-regions-from	Tags2Parts: Discovering Semantic Regions from Shape Tags	1708.06673	http://arxiv.org/abs/1708.06673v3	http://arxiv.org/pdf/1708.06673v3.pdf	https://github.com/sanjeevmk/Tags2Parts	false	false	true	tf
https://paperswithcode.com/paper/capsgan-using-dynamic-routing-for-generative	CapsGAN: Using Dynamic Routing for Generative Adversarial Networks	1806.03968	http://arxiv.org/abs/1806.03968v1	http://arxiv.org/pdf/1806.03968v1.pdf	https://github.com/raeidsaqur/CapsGAN	true	true	true	pytorch
https://paperswithcode.com/paper/on-evaluation-of-the-heun-functions	On evaluation of the Heun functions	1506.03848	http://arxiv.org/abs/1506.03848v1	http://arxiv.org/pdf/1506.03848v1.pdf	https://github.com/motygin/Heun_functions	true	true	true	none
https://paperswithcode.com/paper/feature-pyramid-networks-for-object-detection	Feature Pyramid Networks for Object Detection	1612.03144	http://arxiv.org/abs/1612.03144v2	http://arxiv.org/pdf/1612.03144v2.pdf	https://github.com/YudeWang/UNet-Satellite-Image-Segmentation	false	false	true	tf
https://paperswithcode.com/paper/learning-pose-specific-representations-by	Learning Pose Specific Representations by Predicting Different Views	1804.03390	http://arxiv.org/abs/1804.03390v2	http://arxiv.org/pdf/1804.03390v2.pdf	https://github.com/poier/PreView	false	false	true	pytorch
https://paperswithcode.com/paper/photo-realistic-single-image-super-resolution	Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network	1609.04802	http://arxiv.org/abs/1609.04802v5	http://arxiv.org/pdf/1609.04802v5.pdf	https://github.com/gongenhao/GANCS	false	false	true	tf
https://paperswithcode.com/paper/multi-view-stereo-3d-edge-reconstruction	Multi-View Stereo 3D Edge Reconstruction	1801.05606	http://arxiv.org/abs/1801.05606v1	http://arxiv.org/pdf/1801.05606v1.pdf	https://github.com/abignoli/EdgeGraph3D	true	true	true	none
https://paperswithcode.com/paper/ml-leaks-model-and-data-independent	ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models	1806.01246	http://arxiv.org/abs/1806.01246v2	http://arxiv.org/pdf/1806.01246v2.pdf	https://github.com/katekemu/mia	false	false	true	pytorch
https://paperswithcode.com/paper/a-systematic-evaluation-of-recent-deep	A Systematic Evaluation of Recent Deep Learning Architectures for Fine-Grained Vehicle Classification	1806.02987	http://arxiv.org/abs/1806.02987v1	http://arxiv.org/pdf/1806.02987v1.pdf	https://github.com/OrkhanHI/Grab-AI-Computer-Vision-Challenge	false	false	true	pytorch
https://paperswithcode.com/paper/bert4rec-sequential-recommendation-with	BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer	1904.06690	https://arxiv.org/abs/1904.06690v2	https://arxiv.org/pdf/1904.06690v2.pdf	https://github.com/jaywonchung/BERT4Rec-VAE-Pytorch	false	false	false	pytorch
https://paperswithcode.com/paper/deep-photo-style-transfer	Deep Photo Style Transfer	1703.07511	http://arxiv.org/abs/1703.07511v3	http://arxiv.org/pdf/1703.07511v3.pdf	https://github.com/purushothamgowthu/deep-photo-styletransfer	false	false	true	torch
https://paperswithcode.com/paper/deeplab-semantic-image-segmentation-with-deep	DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs	1606.00915	http://arxiv.org/abs/1606.00915v2	http://arxiv.org/pdf/1606.00915v2.pdf	https://github.com/purushothamgowthu/deep-photo-styletransfer	false	false	true	torch
https://paperswithcode.com/paper/banach-wasserstein-gan	Banach Wasserstein GAN	1806.06621	http://arxiv.org/abs/1806.06621v2	http://arxiv.org/pdf/1806.06621v2.pdf	https://github.com/adler-j/bwgan	true	true	true	tf
https://paperswithcode.com/paper/a-universal-music-translation-network	A Universal Music Translation Network	1805.07848	http://arxiv.org/abs/1805.07848v2	http://arxiv.org/pdf/1805.07848v2.pdf	https://github.com/scpark20/universal-music-translation	false	false	true	tf
https://paperswithcode.com/paper/wavenet-a-generative-model-for-raw-audio	WaveNet: A Generative Model for Raw Audio	1609.03499	http://arxiv.org/abs/1609.03499v2	http://arxiv.org/pdf/1609.03499v2.pdf	https://github.com/scpark20/universal-music-translation	false	false	true	tf
https://paperswithcode.com/paper/can-we-still-avoid-automatic-face-detection	Can we still avoid automatic face detection?	1602.04504	https://arxiv.org/abs/1602.04504v2	https://arxiv.org/pdf/1602.04504v2.pdf	https://github.com/cydonia999/Tiny_Faces_in_Tensorflow	false	false	true	tf
https://paperswithcode.com/paper/difftune-mpc-closed-loop-learning-for-model	DiffTune-MPC: Closed-Loop Learning for Model Predictive Control	2312.11384	https://arxiv.org/abs/2312.11384v3	https://arxiv.org/pdf/2312.11384v3.pdf	https://github.com/sheng-cheng/difftuneopensource	false	false	true	none
https://paperswithcode.com/paper/deep-learning-methods-for-reynolds-averaged	Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows	1810.08217	https://arxiv.org/abs/1810.08217v3	https://arxiv.org/pdf/1810.08217v3.pdf	https://github.com/thunil/Deep-Flow-Prediction	true	true	true	pytorch
https://paperswithcode.com/paper/emulating-spatio-temporal-realizations-of	Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models	2112.03469	https://arxiv.org/abs/2112.03469v1	https://arxiv.org/pdf/2112.03469v1.pdf	https://github.com/MReza89/Emulating-Spatio-Temporal-Realizations-of-Three-Dimensional-Isotropic-Turbulence-via-Deep-Sequence	true	false	true	pytorch
https://paperswithcode.com/paper/iterative-gaussianization-from-ica-to-random	Iterative Gaussianization: from ICA to Random Rotations	1602.00229	http://arxiv.org/abs/1602.00229v1	http://arxiv.org/pdf/1602.00229v1.pdf	https://github.com/spencerkent/pyRBIG	false	false	false	none
https://paperswithcode.com/paper/rl2-fast-reinforcement-learning-via-slow	RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning	1611.02779	http://arxiv.org/abs/1611.02779v2	http://arxiv.org/pdf/1611.02779v2.pdf	https://github.com/dragen1860/MAML-Pytorch-RL	false	false	true	pytorch
https://paperswithcode.com/paper/disentangling-factors-of-variation-in-deep	Disentangling factors of variation in deep representations using adversarial training	1611.03383	http://arxiv.org/abs/1611.03383v1	http://arxiv.org/pdf/1611.03383v1.pdf	https://github.com/ananyahjha93/challenges-in-disentangling	false	false	true	pytorch
https://paperswithcode.com/paper/multi-task-deep-morphological-analyzer	Multi Task Deep Morphological Analyzer: Context Aware Joint Morphological Tagging and Lemma Prediction	1811.08619	https://arxiv.org/abs/1811.08619v2	https://arxiv.org/pdf/1811.08619v2.pdf	https://github.com/Saurav0074/morph_analyzer	true	true	false	none
https://paperswithcode.com/paper/compacter-efficient-low-rank-hypercomplex	Compacter: Efficient Low-Rank Hypercomplex Adapter Layers	2106.04647	https://arxiv.org/abs/2106.04647v2	https://arxiv.org/pdf/2106.04647v2.pdf	https://github.com/rabeehk/compacter	true	true	false	pytorch
https://paperswithcode.com/paper/a-neural-algorithm-of-artistic-style	A Neural Algorithm of Artistic Style	1508.06576	http://arxiv.org/abs/1508.06576v2	http://arxiv.org/pdf/1508.06576v2.pdf	https://github.com/thinkingmachines/christmAIs	false	false	true	tf
https://paperswithcode.com/paper/liar-liar-pants-on-fire-a-new-benchmark	"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection	1705.00648	http://arxiv.org/abs/1705.00648v1	http://arxiv.org/pdf/1705.00648v1.pdf	https://github.com/JelenaBanjac/AppliedDataAnalysis	false	false	true	none
https://paperswithcode.com/paper/learning-multi-level-hierarchies-with	Learning Multi-Level Hierarchies with Hindsight	1712.00948	https://arxiv.org/abs/1712.00948v5	https://arxiv.org/pdf/1712.00948v5.pdf	https://github.com/andrew-j-levy/Hierarchical-Actor-Critc-HAC-	true	true	true	tf
https://paperswithcode.com/paper/a-framework-for-algorithm-deployment-on-cloud	A framework for algorithm deployment on cloud-based quantum computers	1810.10576	http://arxiv.org/abs/1810.10576v1	http://arxiv.org/pdf/1810.10576v1.pdf	https://github.com/hsim13372/QCompress	true	true	true	none
https://paperswithcode.com/paper/no-metrics-are-perfect-adversarial-reward	No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling	1804.09160	http://arxiv.org/abs/1804.09160v2	http://arxiv.org/pdf/1804.09160v2.pdf	https://github.com/littlekobe/AREL	true	true	true	pytorch
https://paperswithcode.com/paper/semantic-instance-segmentation-via-deep	Semantic Instance Segmentation via Deep Metric Learning	1703.10277	http://arxiv.org/abs/1703.10277v1	http://arxiv.org/pdf/1703.10277v1.pdf	https://github.com/alicranck/instance-seg	false	false	true	pytorch

Subsets and Splits

Framework Repo Connectivity Analysis

Reveals the number of official and unofficial repositories and papers associated with different frameworks, highlighting the most connected ones.

Deduplicated Paper-Code Links

This query provides a detailed and organized list of repositories linked to single papers, highlighting official status and mention sources, which is useful for understanding the relationship between papers and their corresponding repositories.

Paper Repo Counts & Distribution

Provides detailed statistics on the distribution of papers across different numbers of repositories, highlighting the percentage of papers with multiple repositories.

Quantum Papers with Code Links

Lists quantum-related papers with their titles, arXiv IDs, frameworks, and code repository links, providing a valuable resource for researchers interested in quantum computing.

Financial Stock Price Prediction

Finds papers related to stock prices, financial markets, and predictions, providing a focused subset for further analysis.

Search for YOLO Links

Retrieves a limited set of records related to YOLO, providing basic information about papers and repositories but without deeper analysis.

Prompt Optimization and Personalization

Retrieves a limited set of papers with titles containing specific keywords related to prompt optimization and personalization, providing basic filtering of the dataset.