Datasets:
pwc-archive
/
links-between-paper-and-code

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/efficient-learning-of-generative-models-via
Efficient Learning of Generative Models via Finite-Difference Score Matching
2007.03317
https://arxiv.org/abs/2007.03317v2
https://arxiv.org/pdf/2007.03317v2.pdf
https://github.com/taufikxu/FD-ScoreMatching
true
true
false
pytorch
https://paperswithcode.com/paper/learning-individualized-treatment-rules-with
Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score
2007.01083
https://arxiv.org/abs/2007.01083v1
https://arxiv.org/pdf/2007.01083v1.pdf
https://github.com/ZhiliangWu/etips
true
true
true
tf
https://paperswithcode.com/paper/gradient-temporal-difference-learning-with
Gradient Temporal-Difference Learning with Regularized Corrections
2007.00611
https://arxiv.org/abs/2007.00611v4
https://arxiv.org/pdf/2007.00611v4.pdf
https://github.com/rlai-lab/Regularized-GradientTD
true
true
true
pytorch
https://paperswithcode.com/paper/deep-bayesian-quadrature-policy-optimization
Deep Bayesian Quadrature Policy Optimization
2006.15637
https://arxiv.org/abs/2006.15637v3
https://arxiv.org/pdf/2006.15637v3.pdf
https://github.com/Akella17/Deep-Bayesian-Quadrature-Policy-Optimization
true
true
true
pytorch
https://paperswithcode.com/paper/gnn3dmot-graph-neural-network-for-3d-multi-1
GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning
2006.07327
https://arxiv.org/abs/2006.07327v1
https://arxiv.org/pdf/2006.07327v1.pdf
https://github.com/xinshuoweng/GNN3DMOT
true
true
false
pytorch
https://paperswithcode.com/paper/rethinking-the-truly-unsupervised-image-to
Rethinking the Truly Unsupervised Image-to-Image Translation
2006.06500
https://arxiv.org/abs/2006.06500v2
https://arxiv.org/pdf/2006.06500v2.pdf
https://github.com/clovaai/tunit
true
true
true
pytorch
https://paperswithcode.com/paper/compositional-convolutional-neural-networks-a
Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion
2003.04490
https://arxiv.org/abs/2003.04490v3
https://arxiv.org/pdf/2003.04490v3.pdf
https://github.com/AdamKortylewski/CompositionalNets
true
true
false
pytorch
https://paperswithcode.com/paper/intra-3d-intracranial-aneurysm-dataset-for
IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning
2003.02920
https://arxiv.org/abs/2003.02920v2
https://arxiv.org/pdf/2003.02920v2.pdf
https://github.com/intra3d2019/IntrA
true
true
true
none
https://paperswithcode.com/paper/few-shot-learning-on-graphs-via-super-classes-1
Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures
2002.12815
https://arxiv.org/abs/2002.12815v1
https://arxiv.org/pdf/2002.12815v1.pdf
https://github.com/chauhanjatin10/GraphsFewShot
true
true
false
pytorch
https://paperswithcode.com/paper/roto-translation-equivariant-convolutional
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis
2002.08725
https://arxiv.org/abs/2002.08725v1
https://arxiv.org/pdf/2002.08725v1.pdf
https://github.com/tueimage/se2cnn
true
true
false
tf
https://paperswithcode.com/paper/efficient-policy-learning-from-surrogate-loss
Efficient Policy Learning from Surrogate-Loss Classification Reductions
2002.05153
https://arxiv.org/abs/2002.05153v1
https://arxiv.org/pdf/2002.05153v1.pdf
https://github.com/CausalML/ESPRM
true
true
true
pytorch
https://paperswithcode.com/paper/detecting-stable-communities-in-link-streams
Detecting Stable Communities in Link Streams at Multiple Temporal Scales
1907.10453
https://arxiv.org/abs/1907.10453v1
https://arxiv.org/pdf/1907.10453v1.pdf
https://github.com/Yquetzal/ECML_PKDD_2019
true
true
false
none
https://paperswithcode.com/paper/reinforcement-learning-enhanced-quantum
Reinforcement Learning Enhanced Quantum-inspired Algorithm for Combinatorial Optimization
2002.04676
https://arxiv.org/abs/2002.04676v2
https://arxiv.org/pdf/2002.04676v2.pdf
https://github.com/BeloborodovDS/SIMCIM-RL
true
true
true
pytorch
https://paperswithcode.com/paper/a-probabilistic-formulation-of-unsupervised-1
A Probabilistic Formulation of Unsupervised Text Style Transfer
2002.03912
https://arxiv.org/abs/2002.03912v3
https://arxiv.org/pdf/2002.03912v3.pdf
https://github.com/cindyxinyiwang/deep-latent-sequence-model
true
true
true
pytorch
https://paperswithcode.com/paper/correcting-knowledge-base-assertions
Correcting Knowledge Base Assertions
2001.06917
https://arxiv.org/abs/2001.06917v1
https://arxiv.org/pdf/2001.06917v1.pdf
https://github.com/ChenJiaoyan/KG_Curation
true
true
false
tf
https://paperswithcode.com/paper/nonparametric-estimation-of-population
Nonparametric Estimation of Population Average Dose-Response Curves using Entropy Balancing Weights for Continuous Exposures
2003.02938
https://arxiv.org/abs/2003.02938v1
https://arxiv.org/pdf/2003.02938v1.pdf
https://github.com/EddieYang211/ebal-python
false
false
true
none
https://paperswithcode.com/paper/learning-fairness-in-multi-agent-systems
Learning Fairness in Multi-Agent Systems
1910.14472
https://arxiv.org/abs/1910.14472v1
https://arxiv.org/pdf/1910.14472v1.pdf
https://github.com/PKU-AI-Edge/FEN
true
true
false
tf
https://paperswithcode.com/paper/a-holistic-approach-to-polyphonic-music
A holistic approach to polyphonic music transcription with neural networks
1910.12086
https://arxiv.org/abs/1910.12086v1
https://arxiv.org/pdf/1910.12086v1.pdf
https://github.com/mangelroman/audio2score
true
true
false
pytorch
https://paperswithcode.com/paper/inherent-weight-normalization-in-stochastic
Inherent Weight Normalization in Stochastic Neural Networks
1910.12316
https://arxiv.org/abs/1910.12316v1
https://arxiv.org/pdf/1910.12316v1.pdf
https://github.com/nmi-lab/neural_sampling_machines
true
true
false
pytorch
https://paperswithcode.com/paper/bottom-up-meta-policy-search
Bottom-Up Meta-Policy Search
1910.10232
https://arxiv.org/abs/1910.10232v2
https://arxiv.org/pdf/1910.10232v2.pdf
https://github.com/luckeciano/bumps
true
true
false
tf
https://paperswithcode.com/paper/meme-generating-rnn-model-explanations-via-1
MEME: Generating RNN Model Explanations via Model Extraction
null
https://openreview.net/forum?id=0beaSUVK_n4
https://openreview.net/pdf?id=0beaSUVK_n4
https://github.com/dmitrykazhdan/MEME-RNN-XAI
true
true
false
tf
https://paperswithcode.com/paper/compacting-picking-and-growing-for
Compacting, Picking and Growing for Unforgetting Continual Learning
1910.06562
https://arxiv.org/abs/1910.06562v3
https://arxiv.org/pdf/1910.06562v3.pdf
https://github.com/ivclab/CPG
true
true
false
pytorch
https://paperswithcode.com/paper/how-does-language-influence-documentation
How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages
1910.05154
https://arxiv.org/abs/1910.05154v1
https://arxiv.org/pdf/1910.05154v1.pdf
https://github.com/mzboito/mmboshi
true
true
true
none
https://paperswithcode.com/paper/smoothfool-an-efficient-framework-for
SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations
1910.03624
https://arxiv.org/abs/1910.03624v1
https://arxiv.org/pdf/1910.03624v1.pdf
https://github.com/alldbi/SmoothFool
true
true
true
pytorch
https://paperswithcode.com/paper/epca-high-dimensional-exponential-family-pca
$e$PCA: High Dimensional Exponential Family PCA
1611.05550
https://arxiv.org/abs/1611.05550v2
https://arxiv.org/pdf/1611.05550v2.pdf
https://github.com/lydiatliu/epca
true
true
true
none
https://paperswithcode.com/paper/biobert-a-pre-trained-biomedical-language
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
1901.08746
https://arxiv.org/abs/1901.08746v4
https://arxiv.org/pdf/1901.08746v4.pdf
https://github.com/jpablou/Matching-The-Blanks-Ths
false
false
true
pytorch
https://paperswithcode.com/paper/generalized-inner-loop-meta-learning
Generalized Inner Loop Meta-Learning
1910.01727
https://arxiv.org/abs/1910.01727v2
https://arxiv.org/pdf/1910.01727v2.pdf
https://github.com/facebookresearch/higher
true
true
false
pytorch
https://paperswithcode.com/paper/albert-a-lite-bert-for-self-supervised
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
1909.11942
https://arxiv.org/abs/1909.11942v6
https://arxiv.org/pdf/1909.11942v6.pdf
https://github.com/jpablou/Matching-The-Blanks-Ths
false
false
true
pytorch
https://paperswithcode.com/paper/mtab-matching-tabular-data-to-knowledge-graph
MTab: Matching Tabular Data to Knowledge Graph using Probability Models
1910.00246
https://arxiv.org/abs/1910.00246v2
https://arxiv.org/pdf/1910.00246v2.pdf
https://github.com/phucty/MTab
true
true
true
none
https://paperswithcode.com/paper/matching-the-blanks-distributional-similarity
Matching the Blanks: Distributional Similarity for Relation Learning
1906.03158
https://arxiv.org/abs/1906.03158v1
https://arxiv.org/pdf/1906.03158v1.pdf
https://github.com/jpablou/Matching-The-Blanks-Ths
false
false
true
pytorch
https://paperswithcode.com/paper/well-calibrated-model-uncertainty-with
Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference
1909.13550
https://arxiv.org/abs/1909.13550v3
https://arxiv.org/pdf/1909.13550v3.pdf
https://github.com/mlaves/bayesian-temperature-scaling
true
true
true
pytorch
https://paperswithcode.com/paper/social-and-scene-aware-trajectory-prediction
Social and Scene-Aware Trajectory Prediction in Crowded Spaces
1909.08840
https://arxiv.org/abs/1909.08840v1
https://arxiv.org/pdf/1909.08840v1.pdf
https://github.com/Oghma/sns-lstm
true
true
false
tf
https://paperswithcode.com/paper/revealing-the-importance-of-semantic
Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
1909.08041
https://arxiv.org/abs/1909.08041v1
https://arxiv.org/pdf/1909.08041v1.pdf
https://github.com/easonnie/semanticRetrievalMRS
true
true
true
pytorch
https://paperswithcode.com/paper/stacking-models-for-nearly-optimal-link
Stacking Models for Nearly Optimal Link Prediction in Complex Networks
1909.07578
https://arxiv.org/abs/1909.07578v1
https://arxiv.org/pdf/1909.07578v1.pdf
https://github.com/Aghasemian/OptimalLinkPrediction
true
true
true
none
https://paperswithcode.com/paper/say-anything-automatic-semantic-infelicity
Say Anything: Automatic Semantic Infelicity Detection in L2 English Indefinite Pronouns
1909.07928
https://arxiv.org/abs/1909.07928v1
https://arxiv.org/pdf/1909.07928v1.pdf
https://github.com/ellarabi/indefinite-pronouns
true
true
false
none
https://paperswithcode.com/paper/basketballgan-generating-basketball-play
BasketballGAN: Generating Basketball Play Simulation Through Sketching
1909.07088
https://arxiv.org/abs/1909.07088v2
https://arxiv.org/pdf/1909.07088v2.pdf
https://github.com/chychen/BasketballGAN
true
true
true
tf
https://paperswithcode.com/paper/efficient-low-rank-gaussian-variational
Efficient Low Rank Gaussian Variational Inference for Neural Networks
null
http://proceedings.neurips.cc/paper/2020/hash/310cc7ca5a76a446f85c1a0d641ba96d-Abstract.html
http://proceedings.neurips.cc/paper/2020/file/310cc7ca5a76a446f85c1a0d641ba96d-Paper.pdf
https://github.com/marctom/elrgvi
true
true
false
pytorch
https://paperswithcode.com/paper/neural-abstractive-text-summarization-with
Neural Abstractive Text Summarization with Sequence-to-Sequence Models
1812.02303
https://arxiv.org/abs/1812.02303v4
https://arxiv.org/pdf/1812.02303v4.pdf
https://github.com/freeflyxiaoma/pycorrector
false
false
true
tf
https://paperswithcode.com/paper/distributional-policy-optimization-an
Distributional Policy Optimization: An Alternative Approach for Continuous Control
1905.09855
https://arxiv.org/abs/1905.09855v2
https://arxiv.org/pdf/1905.09855v2.pdf
https://github.com/tesslerc/GAC
true
true
true
pytorch
https://paperswithcode.com/paper/neural-language-correction-with-character
Neural Language Correction with Character-Based Attention
1603.09727
http://arxiv.org/abs/1603.09727v1
http://arxiv.org/pdf/1603.09727v1.pdf
https://github.com/freeflyxiaoma/pycorrector
false
false
true
tf
https://paperswithcode.com/paper/a-zeroth-order-block-coordinate-descent
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization
2102.10707
https://arxiv.org/abs/2102.10707v2
https://arxiv.org/pdf/2102.10707v2.pdf
https://github.com/YuchenLou/ZO-BCD
true
true
false
none
https://paperswithcode.com/paper/when-a-good-translation-is-wrong-in-context
When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion
1905.05979
https://arxiv.org/abs/1905.05979v2
https://arxiv.org/pdf/1905.05979v2.pdf
https://github.com/lena-voita/good-translation-wrong-in-context
true
true
false
tf
https://paperswithcode.com/paper/190503706
Accurate Visual Localization for Automotive Applications
1905.03706
http://arxiv.org/abs/1905.03706v1
http://arxiv.org/pdf/1905.03706v1.pdf
https://github.com/getnexar/Nexar-Visual-Localization
true
true
true
none
https://paperswithcode.com/paper/lifelong-sequential-modeling-with
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
1905.00758
https://arxiv.org/abs/1905.00758v2
https://arxiv.org/pdf/1905.00758v2.pdf
https://github.com/alimamarankgroup/HPMN
true
true
true
tf
https://paperswithcode.com/paper/data-hand-fostering-visual-exploration-of
Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction
2101.06283
https://arxiv.org/abs/2101.06283v1
https://arxiv.org/pdf/2101.06283v1.pdf
https://github.com/umdsquare/data-at-hand-mobile
true
false
false
none
https://paperswithcode.com/paper/190411800
Adaptive Matrix Completion for the Users and the Items in Tail
1904.11800
https://arxiv.org/abs/1904.11800v2
https://arxiv.org/pdf/1904.11800v2.pdf
https://github.com/mohit-shrma/matfac
true
true
false
none
https://paperswithcode.com/paper/190409324
Mask-Predict: Parallel Decoding of Conditional Masked Language Models
1904.09324
https://arxiv.org/abs/1904.09324v2
https://arxiv.org/pdf/1904.09324v2.pdf
https://github.com/facebookresearch/Mask-Predict
true
true
false
pytorch
https://paperswithcode.com/paper/neural-message-passing-for-multi-label-1
Neural Message Passing for Multi-Label Classification
1904.08049
http://arxiv.org/abs/1904.08049v1
http://arxiv.org/pdf/1904.08049v1.pdf
https://github.com/QData/LaMP
true
true
true
pytorch
https://paperswithcode.com/paper/difficulty-aware-image-super-resolution-via
Difficulty-aware Image Super Resolution via Deep Adaptive Dual-Network
1904.05802
http://arxiv.org/abs/1904.05802v2
http://arxiv.org/pdf/1904.05802v2.pdf
https://github.com/xzwlx/Difficulty-SR
true
true
false
pytorch
https://paperswithcode.com/paper/remasc-realistic-replay-attack-corpus-for
ReMASC: Realistic Replay Attack Corpus for Voice Controlled Systems
1904.03365
https://arxiv.org/abs/1904.03365v2
https://arxiv.org/pdf/1904.03365v2.pdf
https://github.com/YuanGongND/ReMASC
true
true
true
pytorch
https://paperswithcode.com/paper/an-open-source-toolkit-for-the-tracking
An open source toolkit for the tracking, termination and recovery of high altitude balloon flights and payloads
1904.04321
http://arxiv.org/abs/1904.04321v1
http://arxiv.org/pdf/1904.04321v1.pdf
https://github.com/PaulZC/Balloon_Cut-Down_Device
true
true
true
none
https://paperswithcode.com/paper/vest-very-sparse-tucker-factorization-of
VeST: Very Sparse Tucker Factorization of Large-Scale Tensors
1904.02603
http://arxiv.org/abs/1904.02603v1
http://arxiv.org/pdf/1904.02603v1.pdf
https://github.com/leesael/VeST
true
true
true
none
https://paperswithcode.com/paper/et-bert-a-contextualized-datagram
ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification
2202.06335
https://arxiv.org/abs/2202.06335v2
https://arxiv.org/pdf/2202.06335v2.pdf
https://github.com/linwhitehat/et-bert
true
true
true
pytorch
https://paperswithcode.com/paper/robust-graph-learning-from-noisy-data
Robust Graph Learning from Noisy Data
1812.06673
http://arxiv.org/abs/1812.06673v1
http://arxiv.org/pdf/1812.06673v1.pdf
https://github.com/sckangz/RGC
true
true
false
none
https://paperswithcode.com/paper/lsicc-a-large-scale-informal-chinese-corpus
LSICC: A Large Scale Informal Chinese Corpus
1811.10167
http://arxiv.org/abs/1811.10167v1
http://arxiv.org/pdf/1811.10167v1.pdf
https://github.com/JaniceZhao/Chinese-Forum-Corpus
true
true
false
none
https://paperswithcode.com/paper/using-sentiment-induction-to-understand
Using Sentiment Induction to Understand Variation in Gendered Online Communities
1811.07061
http://arxiv.org/abs/1811.07061v1
http://arxiv.org/pdf/1811.07061v1.pdf
https://github.com/lucy3/reddit-sent
true
true
false
none
https://paperswithcode.com/paper/on-pruning-for-score-based-bayesian-network
On Pruning for Score-Based Bayesian Network Structure Learning
1905.09943
https://arxiv.org/abs/1905.09943v2
https://arxiv.org/pdf/1905.09943v2.pdf
https://github.com/AlCorreia/BDeu-Structure-Learning
true
false
false
none
https://paperswithcode.com/paper/derpn-taking-a-further-step-toward-more
DeRPN: Taking a further step toward more general object detection
1811.06700
http://arxiv.org/abs/1811.06700v1
http://arxiv.org/pdf/1811.06700v1.pdf
https://github.com/HCIILAB/DeRPN
true
true
true
none
https://paperswithcode.com/paper/counterfactual-learning-from-human
Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing
1811.12239
http://arxiv.org/abs/1811.12239v1
http://arxiv.org/pdf/1811.12239v1.pdf
https://github.com/carolinlawrence/nematus
true
false
false
none
https://paperswithcode.com/paper/gated-hierarchical-attention-for-image
Gated Hierarchical Attention for Image Captioning
1810.12535
http://arxiv.org/abs/1810.12535v2
http://arxiv.org/pdf/1810.12535v2.pdf
https://github.com/qingzwang/GHA-ImageCaptioning
true
true
true
pytorch
https://paperswithcode.com/paper/global-deep-learning-methods-for
Non-local U-Net for Biomedical Image Segmentation
1812.04103
https://arxiv.org/abs/1812.04103v2
https://arxiv.org/pdf/1812.04103v2.pdf
https://github.com/divelab/Non-local-U-Nets
true
true
false
tf
https://paperswithcode.com/paper/context-dependent-word-representation-for
Context-Dependent Word Representation for Neural Machine Translation
1607.00578
http://arxiv.org/abs/1607.00578v1
http://arxiv.org/pdf/1607.00578v1.pdf
https://github.com/kyunghyuncho/WordVectorManifold
true
true
false
none
https://paperswithcode.com/paper/interactive-language-learning-by-question
Interactive Language Learning by Question Answering
1908.10909
https://arxiv.org/abs/1908.10909v1
https://arxiv.org/pdf/1908.10909v1.pdf
https://github.com/xingdi-eric-yuan/qait_public
true
true
false
pytorch
https://paperswithcode.com/paper/building-a-hebrew-semantic-role-labeling
Building a Hebrew Semantic Role Labeling Lexical Resource from Parallel Movie Subtitles
2005.08206
https://arxiv.org/abs/2005.08206v1
https://arxiv.org/pdf/2005.08206v1.pdf
https://github.com/bgunlp/hebrew_srl
true
true
false
none
https://paperswithcode.com/paper/data-driven-meta-set-based-fine-grained
Data-driven Meta-set Based Fine-Grained Visual Classification
2008.02438
https://arxiv.org/abs/2008.02438v1
https://arxiv.org/pdf/2008.02438v1.pdf
https://github.com/NUST-Machine-Intelligence-Laboratory/dmbfgvr
true
true
false
pytorch
https://paperswithcode.com/paper/survae-flows-surjections-to-bridge-the-gap
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
2007.02731
https://arxiv.org/abs/2007.02731v2
https://arxiv.org/pdf/2007.02731v2.pdf
https://github.com/didriknielsen/survae_flows
true
true
true
pytorch
https://paperswithcode.com/paper/foreground-segmentation-using-a-triplet
Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding
1801.02225
http://arxiv.org/abs/1801.02225v1
http://arxiv.org/pdf/1801.02225v1.pdf
https://github.com/lim-anggun/FgSegNet
true
true
true
tf
https://paperswithcode.com/paper/morphological-analyzer-and-generator-for
Morphological Analyzer and Generator for Russian and Ukrainian Languages
1503.07283
http://arxiv.org/abs/1503.07283v1
http://arxiv.org/pdf/1503.07283v1.pdf
https://github.com/kmike/pymorphy2
true
true
true
none
https://paperswithcode.com/paper/how-to-find-a-unicorn-a-novel-model-free
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series
2004.11468
https://arxiv.org/abs/2004.11468v3
https://arxiv.org/pdf/2004.11468v3.pdf
https://github.com/phrenico/uniqed
true
true
true
none
https://paperswithcode.com/paper/image-to-image-translation-via-group-wise
Image-to-Image Translation via Group-wise Deep Whitening-and-Coloring Transformation
1812.09912
https://arxiv.org/abs/1812.09912v2
https://arxiv.org/pdf/1812.09912v2.pdf
https://github.com/WonwoongCho/GDWCT
true
true
true
pytorch
https://paperswithcode.com/paper/modular-representation-underlies-systematic
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation
2004.14623
https://arxiv.org/abs/2004.14623v4
https://arxiv.org/pdf/2004.14623v4.pdf
https://github.com/atticusg/MoNLI
true
true
false
none
https://paperswithcode.com/paper/modelicagym-applying-reinforcement-learning
ModelicaGym: Applying Reinforcement Learning to Modelica Models
1909.08604
https://arxiv.org/abs/1909.08604v1
https://arxiv.org/pdf/1909.08604v1.pdf
https://github.com/ucuapps/modelicagym
true
true
true
none
https://paperswithcode.com/paper/finding-temporal-patterns-using-algebraic
Finding path motifs in large temporal graphs using algebraic fingerprints
2001.07158
https://arxiv.org/abs/2001.07158v4
https://arxiv.org/pdf/2001.07158v4.pdf
https://github.com/suhastheju/temporal-patterns-mk2
true
true
false
none
https://paperswithcode.com/paper/towards-precise-completion-of-deformable
Towards Precise Completion of Deformable Shapes
null
https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4619_ECCV_2020_paper.php
https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690358.pdf
https://github.com/OshriHalimi/precise_shape_completion
true
true
false
none
https://paperswithcode.com/paper/towards-compact-single-image-super-resolution
Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
2105.11683
https://arxiv.org/abs/2105.11683v1
https://arxiv.org/pdf/2105.11683v1.pdf
https://github.com/mindspore-ai/contrib/tree/master/papers/CSD
false
false
false
mindspore
https://paperswithcode.com/paper/eigendecompositions-of-transfer-operators-in
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces
1712.01572
https://arxiv.org/abs/1712.01572v3
https://arxiv.org/pdf/1712.01572v3.pdf
https://github.com/sklus/d3s
true
true
false
none
https://paperswithcode.com/paper/a-genre-aware-attention-model-to-improve-the
A Genre-Aware Attention Model to Improve the Likability Prediction of Books
null
https://aclanthology.org/D18-1375
https://aclanthology.org/D18-1375.pdf
https://github.com/sjmaharjan/genre_aware_attention
true
true
false
none
https://paperswithcode.com/paper/prema-principled-tensor-data-recovery-from
PREMA: Principled Tensor Data Recovery from Multiple Aggregated Views
1910.12001
https://arxiv.org/abs/1910.12001v2
https://arxiv.org/pdf/1910.12001v2.pdf
https://github.com/FaisalAlmutairi/Prema
true
true
true
none
https://paperswithcode.com/paper/learning-to-generate-move-by-move-commentary
Learning to Generate Move-by-Move Commentary for Chess Games from Large-Scale Social Forum Data
null
https://aclanthology.org/P18-1154
https://aclanthology.org/P18-1154.pdf
https://github.com/harsh19/ChessCommentaryGeneration
true
true
false
pytorch
https://paperswithcode.com/paper/interactive-text-ranking-with-bayesian
Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation
1911.10183
https://arxiv.org/abs/1911.10183v3
https://arxiv.org/pdf/1911.10183v3.pdf
https://github.com/UKPLab/tacl2020-interactive-ranking
true
true
false
pytorch
https://paperswithcode.com/paper/wavelet-integrated-cnns-for-noise-robust
Wavelet Integrated CNNs for Noise-Robust Image Classification
2005.03337
https://arxiv.org/abs/2005.03337v2
https://arxiv.org/pdf/2005.03337v2.pdf
https://github.com/LiQiufu/WaveCNet
true
true
false
pytorch
https://paperswithcode.com/paper/generating-market-comments-referring-to
Generating Market Comments Referring to External Resources
null
https://aclanthology.org/W18-6515
https://aclanthology.org/W18-6515.pdf
https://github.com/aistairc/market-reporter
true
true
false
pytorch
https://paperswithcode.com/paper/comment-on-androdet-an-adaptive-android
Comment on "AndrODet: An adaptive Android obfuscation detector"
1910.06192
https://arxiv.org/abs/1910.06192v2
https://arxiv.org/pdf/1910.06192v2.pdf
https://github.com/alirezamohammadinodooshan/androdet-se-eval
true
true
false
none
https://paperswithcode.com/paper/real-world-multiobject-multigrasp-detection
Real-world multiobject, multigrasp detection
null
https://arxiv.org/abs/1802.00520
https://arxiv.org/pdf/1802.00520.pdf
https://github.com/ivalab/grasp_multiObject
true
true
false
none
https://paperswithcode.com/paper/unsupervised-feature-learning-via-non-1
Unsupervised Feature Learning via Non-Parametric Instance Discrimination
null
http://openaccess.thecvf.com/content_cvpr_2018/html/Wu_Unsupervised_Feature_Learning_CVPR_2018_paper.html
http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Unsupervised_Feature_Learning_CVPR_2018_paper.pdf
https://github.com/zhirongw/lemniscate.pytorch
true
true
false
pytorch
https://paperswithcode.com/paper/zipper-logic
Zipper logic
1405.6095
https://arxiv.org/abs/1405.6095v1
https://arxiv.org/pdf/1405.6095v1.pdf
https://github.com/mbuliga/zss
false
false
true
none
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/sivaole/Face_Detection
false
false
true
tf
https://paperswithcode.com/paper/reinforcement-learning-with-prototypical-1
Reinforcement Learning with Prototypical Representations
null
https://openreview.net/forum?id=NVd9b1sFO0R
https://openreview.net/pdf?id=NVd9b1sFO0R
https://github.com/denisyarats/proto
true
true
false
pytorch
https://paperswithcode.com/paper/evaluating-bayesian-deep-learning-methods-for
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation
1811.12709
http://arxiv.org/abs/1811.12709v2
http://arxiv.org/pdf/1811.12709v2.pdf
https://github.com/IntelLabs/AVUC
false
false
true
pytorch
https://paperswithcode.com/paper/your-answer-is-incorrect-would-you-like-to-1
Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset
null
https://aclanthology.org/2022.acl-long.587
https://aclanthology.org/2022.acl-long.587.pdf
https://github.com/sebochs/saf
true
true
false
pytorch
https://paperswithcode.com/paper/online-geolocalized-emotion-across-us-cities
Online geolocalized emotion across US cities during the COVID crisis: Universality, policy response, and connection with local mobility
2009.10461
https://arxiv.org/abs/2009.10461v1
https://arxiv.org/pdf/2009.10461v1.pdf
https://github.com/aleckirkley/US-covid-tweets-with-sentiments-and-geolocations
true
true
true
none
https://paperswithcode.com/paper/pre-training-auto-generated-volumetric-shapes
Pre-Training Auto-Generated Volumetric Shapes for 3D Medical Image Segmentation
null
https://openaccess.thecvf.com/content/CVPR2023W/ECV/html/Tadokoro_Pre-Training_Auto-Generated_Volumetric_Shapes_for_3D_Medical_Image_Segmentation_CVPRW_2023_paper.html
https://openaccess.thecvf.com/content/CVPR2023W/ECV/papers/Tadokoro_Pre-Training_Auto-Generated_Volumetric_Shapes_for_3D_Medical_Image_Segmentation_CVPRW_2023_paper.pdf
https://github.com/super-tadory/primgeoseg
false
false
false
pytorch
https://paperswithcode.com/paper/comparison-by-conversion-reverse-engineering
Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics
2011.00834
https://arxiv.org/abs/2011.00834v1
https://arxiv.org/pdf/2011.00834v1.pdf
https://github.com/danielhers/hit-scir-ucca-parser
true
true
false
pytorch
https://paperswithcode.com/paper/bracketing-encodings-for-2-planar-dependency
Bracketing Encodings for 2-Planar Dependency Parsing
2011.00596
https://arxiv.org/abs/2011.00596v2
https://arxiv.org/pdf/2011.00596v2.pdf
https://github.com/mstrise/dep2label
true
true
false
pytorch
https://paperswithcode.com/paper/a-unifying-theory-of-transition-based-and
A Unifying Theory of Transition-based and Sequence Labeling Parsing
2011.00584
https://arxiv.org/abs/2011.00584v1
https://arxiv.org/pdf/2011.00584v1.pdf
https://github.com/mstrise/dep2label
true
true
false
pytorch
https://paperswithcode.com/paper/transitive-learning-exploring-the
Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolution
2103.15290
https://arxiv.org/abs/2103.15290v2
https://arxiv.org/pdf/2103.15290v2.pdf
https://github.com/YuanfeiHuang/TLSR
true
true
true
pytorch
https://paperswithcode.com/paper/learning-to-play-cup-and-ball-with-noisy
Learning to Play Cup-and-Ball with Noisy Camera Observations
2007.09562
https://arxiv.org/abs/2007.09562v1
https://arxiv.org/pdf/2007.09562v1.pdf
https://github.com/MPC-Berkeley/kendama
true
true
true
none
https://paperswithcode.com/paper/an-implementation-of-faster-rcnn-with-study
An Implementation of Faster RCNN with Study for Region Sampling
1702.02138
http://arxiv.org/abs/1702.02138v2
http://arxiv.org/pdf/1702.02138v2.pdf
https://github.com/tigerofmurder/tf-faster-rcnn
false
false
true
tf
https://paperswithcode.com/paper/faster-r-cnn-towards-real-time-object
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
1506.01497
http://arxiv.org/abs/1506.01497v3
http://arxiv.org/pdf/1506.01497v3.pdf
https://github.com/tigerofmurder/tf-faster-rcnn
false
false
true
tf
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/tigerofmurder/tf-faster-rcnn
false
false
true
tf