Papers
11,951 papers found
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
Ossama Ahmed, Frederik Träuble, Anirudh Goyal et al.
CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation
Xin Ding, Yongwei Wang, Zuheng Xu et al.
Certify or Predict: Boosting Certified Robustness with Compositional Architectures
Mark Niklas Mueller, Mislav Balunovic, Martin Vechev
Chaos of Learning Beyond Zero-sum and Coordination via Game Decompositions
Yun Kuen Cheung, Yixin Tao
Characterizing signal propagation to close the performance gap in unnormalized ResNets
Andrew Brock, Soham De, Samuel L Smith
Chinese Character Image Clustering and Classification Based on Object Embedding Model (Student Abstract)
Mengting Wang, Xun Liang, Yang Xue
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan et al.
Clairvoyance: A Pipeline Toolkit for Medical Time Series
Daniel Jarrett, Jinsung Yoon, Ioana Bica et al.
Class Normalization for (Continual)? Generalized Zero-Shot Learning
Ivan Skorokhodov, Mohamed Elhoseiny
C-Learning: Horizon-Aware Cumulative Accessibility Estimation
Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner et al.
C-Learning: Learning to Achieve Goals via Recursive Classification
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
Yaling Tao, Kentaro Takagi, Kouta Nakata
CO2: Consistent Contrast for Unsupervised Visual Representation Learning
Chen Wei, Huiyu Wang, Wei Shen et al.
CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers
SHIYANG LI, Semih Yavuz, Kazuma Hashimoto et al.
CoCon: A Self-Supervised Approach for Controlled Text Generation
Alvin Chan, Yew-Soon Ong, Bill Pung et al.
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding
Yanru Qu, Dinghan Shen, Yelong Shen et al.
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
Jan Schuchardt, Aleksandar Bojchevski, Johannes Gasteiger et al.
Colorization Transformer
Manoj Kumar, Dirk Weissenborn, Nal Kalchbrenner
Combining Ensembles and Data Augmentation Can Harm Your Calibration
Yeming Wen, Ghassen Jerfel, Rafael Muller et al.
Combining Label Propagation and Simple Models out-performs Graph Neural Networks
Qian Huang, Horace He, Abhay Singh et al.
Combining Physics and Machine Learning for Network Flow Estimation
Arlei Lopes da Silva, Furkan Kocayusufoglu, Saber Jafarpour et al.
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
JangHyun Kim, Wonho Choo, Hosan Jeong et al.
Communication-efficient and Scalable Decentralized Federated Edge Learning
Austine Zong Han Yapp, Hong Soo Nicholas Koh, Yan Ting Lai et al.
Communication in Multi-Agent Reinforcement Learning: Intention Sharing
Woojun Kim, Jongeui Park, Youngchul Sung
Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini et al.