Papers
Scalable Normalizing Flows for Permutation Invariant Densities
Marin Biloš, Stephan Günnemann
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
Johannes Gasteiger, Marten Lienen, Stephan Günnemann
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Gordon Gordon Wilson et al.
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Muhammad A Rahman et al.
Scaling Properties of Deep Residual Networks
Alain-Sam Cohen, Rama Cont, Alain Rossier et al.
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia, Yinfei Yang, Ye Xia et al.
SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao Song, Penghui Qi et al.
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies
Linxi Fan, Guanzhi Wang, De-An Huang et al.
Segmenting Hybrid Trajectories using Latent ODEs
Ruian Shi, Quaid Morris
Selecting Data Augmentation for Simulating Interventions
Maximilian Ilse, Jakub M Tomczak, Patrick Forré
Self-Damaging Contrastive Learning
Ziyu Jiang, Tianlong Chen, Bobak J Mortazavi et al.
Self-Improved Retrosynthetic Planning
Junsu Kim, Sungsoo Ahn, Hankook Lee et al.
Selfish Sparse RNN Training
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei et al.
Self Normalizing Flows
Thomas A Keller, Jorn W.T. Peters, Priyank Jaini et al.
Self-Paced Context Evaluation for Contextual Reinforcement Learning
Theresa Eimer, André Biedenkapp, Frank Hutter et al.
Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
Yong Cheng, Wei Wang, Lu Jiang et al.
Self-supervised Graph-level Representation Learning with Local and Global Structure
Minghao Xu, Hang Wang, Bingbing Ni et al.
Self-Tuning for Data-Efficient Deep Learning
Ximei Wang, Jinghan Gao, Mingsheng Long et al.
Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
Bahar Taskesen, Man-Chung Yue, Jose Blanchet et al.
SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy Samples
Anshoo Tandon, Aldric Han, Vincent Tan
SGLB: Stochastic Gradient Langevin Boosting
Aleksei Ustimenko, Liudmila Prokhorenkova
SG-PALM: a Fast Physically Interpretable Tensor Graphical Model
Yu Wang, Alfred Hero
Sharf: Shape-conditioned Radiance Fields from a Single View
Konstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari
Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer
Seungwon Lee, Sima Behpour, Eric Eaton
Sharper Generalization Bounds for Clustering
Shaojie Li, Yong Liu