Papers
11,015 papers found
Dynamic Time Lag Regression: Predicting What & When
Mandar Chandorkar, Cyril Furtlehner, Bala Poduval et al.
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality
Saurabh Khanna, Vincent Y. F. Tan
Editable Neural Networks
Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Pyrkin et al.
Effect of Activation Functions on the Training of Overparametrized Neural Nets
Abhishek Panigrahi, Abhishek Shetty, Navin Goyal
Efficient and Information-Preserving Future Frame Prediction and Beyond
Wei Yu, Yichao Lu, Steve Easterbrook et al.
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Yuyu Zhang, Xinshi Chen, Yuan Yang et al.
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform
Jun Li, Fuxin Li, Sinisa Todorovic
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le et al.
Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks
Christopher J. Cueva, Peter Y. Wang, Matthew Chin et al.
Emergent Tool Use From Multi-Agent Autocurricula
Bowen Baker, Ingmar Kanitscheider, Todor Markov et al.
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks
Sanchari Sen, Balaraman Ravindran, Anand Raghunathan
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
Shell Xu Hu, Pablo Garcia Moreno, Yang Xiao et al.
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks
Xiao Zhang, Dongrui Wu
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation
Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda et al.
Encoding word order in complex embeddings
Benyou Wang, Donghao Zhao, Christina Lioma et al.
End to End Trainable Active Contours via Differentiable Rendering
Shir Gur, Tal Shaharabany, Lior Wolf
Energy-based models for atomic-resolution protein conformations
Yilun Du, Joshua Meier, Jerry Ma et al.
Enhancing Adversarial Defense by k-Winners-Take-All
Chang Xiao, Peilin Zhong, Changxi Zheng
Enhancing Transformation-Based Defenses Against Adversarial Attacks with a Distribution Classifier
Connie Kou, Hwee Kuan Lee, Ee-Chien Chang et al.
Ensemble Distribution Distillation
Andrey Malinin, Bruno Mlodozeniec, Mark Gales
Environmental drivers of systematicity and generalization in a situated agent
Felix Hill, Andrew Lampinen, Rosalia Schneider et al.
Episodic Reinforcement Learning with Associative Memory
Guangxiang Zhu*, Zichuan Lin*, Guangwen Yang et al.
Escaping Saddle Points Faster with Stochastic Momentum
Jun-Kun Wang, Chi-Heng Lin, Jacob Abernethy
ES-MAML: Simple Hessian-Free Meta Learning
Xingyou Song, Wenbo Gao, Yuxiang Yang et al.
Estimating counterfactual treatment outcomes over time through adversarially balanced representations
Ioana Bica, Ahmed M Alaa, James Jordon et al.