Papers
11,951 papers found
Efficient Wasserstein Natural Gradients for Reinforcement Learning
Ted Moskovitz, Michael Arbel, Ferenc Huszar et al.
EigenGame: PCA as a Nash Equilibrium
Ian Gemp, Brian McWilliams, Claire Vernade et al.
Emergent Road Rules In Multi-Agent Driving Environments
Avik Pal, Jonah Philion, Yuan-Hong Liao et al.
Emergent Symbols through Binding in External Memory
Taylor Whittington Webb, Ishan Sinha, Jonathan Cohen
Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition
Yangming Li, lemao liu, Shuming Shi
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
Kartik Ahuja, Jun Wang, Amit Dhurandhar et al.
End-to-end Adversarial Text-to-Speech
Jeff Donahue, Sander Dieleman, Mikolaj Binkowski et al.
End-to-End Egospheric Spatial Memory
Daniel James Lenton, Stephen James, Ronald Clark et al.
Enforcing robust control guarantees within neural network policies
Priya L. Donti, Melrose Roderick, Mahyar Fazlyab et al.
Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation
Peiye Zhuang, Oluwasanmi O Koyejo, Alex Schwing
Entropic gradient descent algorithms and wide flat minima
Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer et al.
Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors
Ali Harakeh, Steven L. Waslander
Estimating informativeness of samples with Smooth Unique Information
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini et al.
Estimating Lipschitz constants of monotone deep equilibrium models
Chirag Pabbaraju, Ezra Winston, J Zico Kolter
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology
Sharon Zhou, Eric Zelikman, Fred Lu et al.
EVALUATION OF NEURAL ARCHITECTURES TRAINED WITH SQUARE LOSS VS CROSS-ENTROPY IN CLASSIFICATION TASKS
Like Hui, Mikhail Belkin
Evaluation of Similarity-based Explanations
Kazuaki Hanawa, Sho Yokoi, Satoshi Hara et al.
Evaluations and Methods for Explanation through Robustness Analysis
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu et al.
Evolving Reinforcement Learning Algorithms
John D Co-Reyes, Yingjie Miao, Daiyi Peng et al.
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization
Judy Borowski, Roland Simon Zimmermann, Judith Schepers et al.
Explainable Deep One-Class Classification
Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen et al.
Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs
Zhen Han, Peng Chen, Yunpu Ma et al.
Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning
Alihan Hüyük, Daniel Jarrett, Cem Tekin et al.
Explaining the Efficacy of Counterfactually Augmented Data
Divyansh Kaushik, Amrith Setlur, Eduard H Hovy et al.