Papers
11,951 papers found
Learning Hierarchical Structures with Differentiable Nondeterministic Stacks
Brian DuSell, David Chiang
Learning Long-Term Reward Redistribution via Randomized Return Decomposition
Zhizhou Ren, Ruihan Guo, Yuan Zhou et al.
Learning meta-features for AutoML
Herilalaina Rakotoarison, Louisot Milijaona, Andry RASOANAIVO et al.
Learning more skills through optimistic exploration
DJ Strouse, Kate Baumli, David Warde-Farley et al.
Learning Multimodal VAEs through Mutual Supervision
Tom Joy, Yuge Shi, Philip Torr et al.
Learning Neural Contextual Bandits through Perturbed Rewards
Yiling Jia, Weitong ZHANG, Dongruo Zhou et al.
Learning Object-Oriented Dynamics for Planning from Text
Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand et al.
Learning Optimal Conformal Classifiers
David Stutz, Krishnamurthy Dj Dvijotham, Ali Taylan Cemgil et al.
Learning Prototype-oriented Set Representations for Meta-Learning
Dan dan Guo, Long Tian, Minghe Zhang et al.
Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, And No Retraining
Miao Lu, Xiaolong Luo, Tianlong Chen et al.
Learning Realistic Patterns from Visually Unrealistic Stimuli: Generalization and Data Anonymization (Extended Abstract)
Konstantinos Nikolaidis, Stein Kristiansen, Thomas Plagemann et al.
Learning Representation from Neural Fisher Kernel with Low-rank Approximation
Ruixiang ZHANG, Shuangfei Zhai, Etai Littwin et al.
Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs
Yaoxin Wu, Wen Song, Zhiguang Cao et al.
Learning State Representations via Retracing in Reinforcement Learning
Changmin Yu, Dong Li, Jianye HAO et al.
Learning Strides in Convolutional Neural Networks
Rachid Riad, Olivier Teboul, David Grangier et al.
Learning Super-Features for Image Retrieval
Philippe Weinzaepfel, Thomas Lucas, Diane Larlus et al.
Learning Synthetic Environments and Reward Networks for Reinforcement Learning
Fabio Ferreira, Thomas Nierhoff, Andreas Sälinger et al.
Learning Temporally Causal Latent Processes from General Temporal Data
Weiran Yao, Yuewen Sun, Alex Ho et al.
Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks
Marten Lienen, Stephan Günnemann
Learning to Annotate Part Segmentation with Gradient Matching
Yu Yang, Xiaotian Cheng, Hakan Bilen et al.
Learning to Complete Code with Sketches
Daya Guo, Alexey Svyatkovskiy, Jian Yin et al.
Learning to Dequantise with Truncated Flows
Shawn Tan, Chin-Wei Huang, Alessandro Sordoni et al.
Learning to Downsample for Segmentation of Ultra-High Resolution Images
Chen Jin, Ryutaro Tanno, Thomy Mertzanidou et al.
Learning to Extend Molecular Scaffolds with Structural Motifs
Krzysztof Maziarz, Henry Richard Jackson-Flux, Pashmina Cameron et al.
Learning to Generalize across Domains on Single Test Samples
Zehao Xiao, Xiantong Zhen, Ling Shao et al.