Papers
11,951 papers found
Learning Robust Representations via Multi-View Information Bottleneck
Marco Federici, Anjan Dutta, Patrick Forré et al.
Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling
Yuping Luo, Huazhe Xu, Tengyu Ma
Learning Space Partitions for Nearest Neighbor Search
Yihe Dong, Piotr Indyk, Ilya Razenshteyn et al.
Learning the Arrow of Time for Problems in Reinforcement Learning
Nasim Rahaman, Steffen Wolf, Anirudh Goyal et al.
Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
Divyansh Kaushik, Eduard Hovy, Zachary Lipton
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks
Hae Beom Lee, Hayeon Lee, Donghyun Na et al.
Learning to Control PDEs with Differentiable Physics
Philipp Holl, Nils Thuerey, Vladlen Koltun
Learning to Coordinate Manipulation Skills via Skill Behavior Diversification
Youngwoon Lee, Jingyun Yang, Joseph J. Lim
Learning To Explore Using Active Neural SLAM
Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta et al.
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories
Tiange Luo, Kaichun Mo, Zhiao Huang et al.
Learning to Guide Random Search
Ozan Sener, Vladlen Koltun
Learning to Learn by Zeroth-Order Oracle
Yangjun Ruan, Yuanhao Xiong, Sashank Reddi et al.
Learning to Link
Maria-Florina Balcan, Travis Dick, Manuel Lang
Learning to Move with Affordance Maps
William Qi, Ravi Teja Mullapudi, Saurabh Gupta et al.
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees
Binghong Chen, Bo Dai, Qinjie Lin et al.
Learning to Represent Programs with Property Signatures
Augustus Odena, Charles Sutton
Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi et al.
Learning to solve the credit assignment problem
Benjamin James Lansdell, Prashanth Ravi Prakash, Konrad Paul Kording
Learning transport cost from subset correspondence
Ruishan Liu, Akshay Balsubramani, James Zou
Learning with minibatch Wasserstein : asymptotic and gradient properties
Kilian Fatras, Younes Zine, Rémi Flamary et al.
Learn to Explain Efficiently via Neural Logic Inductive Learning
Yuan Yang, Le Song
Lifted Weight Learning of Markov Logic Networks (Revisited One More Time)
Ondrej Kuzelka, Vyacheslav Kungurtsev, Yuyi Wang
Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware
Xiandong Zhao, Ying Wang, Xuyi Cai et al.
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization
Fabian Latorre, Paul Rolland, Volkan Cevher