Papers
938 papers found
ReZero is all you need: fast convergence at large depth
Thomas Bachlechner, Bodhisattwa Prasad Majumder, Henry Mao et al.
RISAN: Robust instance specific deep abstention network
Bhavya Kalra, Kulin Shah, Naresh Manwani
Robust principal component analysis for generalized multi-view models
Frank Nussbaum, Joachim Giesen
Robust reinforcement learning under minimax regret for green security
Lily Xu, Andrew Perrault, Fei Fang et al.
Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splitting
Adam D. Cobb, Brian Jalaian
SDM-Net: A simple and effective model for generalized zero-shot learning
Shabnam Daghaghi, Tharun Medini, Anshumali Shrivastava
Sequential core-set Monte Carlo
Boyan Beronov, Christian Weilbach, Frank Wood et al.
SGD with low-dimensional gradients with applications to private and distributed learning
Shiva Prasad Kasiviswanathan
Similarity measure for sparse time course data based on Gaussian processes
Zijing Liu, Mauricio Barahona
Sketching curvature for efficient out-of-distribution detection for deep neural networks
Apoorva Sharma, Navid Azizan, Marco Pavone
Sparse linear networks with a fixed butterfly structure: theory and practice
Nir Ailon, Omer Leibovitch, Vineet Nair
Statistically robust neural network classification
Benjie Wang, Stefan Webb, Tom Rainforth
Statistical mechanical analysis of neural network pruning
Rupam Acharyya, Ankani Chattoraj, Boyu Zhang et al.
Staying in shape: learning invariant shape representations using contrastive learning
Jeffrey Gu, Serena Yeung
Stochastic continuous normalizing flows: training SDEs as ODEs
Liam Hodgkinson, Chris van der Heide, Fred Roosta et al.
Stochastic model for sunk cost bias
Jon Kleinberg, Sigal Oren, Manish Raghavan et al.
Strategically efficient exploration in competitive multi-agent reinforcement learning
Robert Loftin, Aadirupa Saha, Sam Devlin et al.
Structured sparsification with joint optimization of group convolution and channel shuffle
Xin-Yu Zhang, Kai Zhao, Taihong Xiao et al.
Subseasonal climate prediction in the western US using Bayesian spatial models
Vishwak Srinivasan, Justin Khim, Arindam Banerjee et al.
Subset-of-data variational inference for deep Gaussian-processes regression
Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan
Sum-product laws and efficient algorithms for imprecise Markov chains
Jasper De Bock, Alexander Erreygers, Thomas Krak
Symmetric Wasserstein autoencoders
Sun Sun, Hongyu Guo
Task similarity aware meta learning: theory-inspired improvement on MAML
Pan Zhou, Yingtian Zou, Xiao-Tong Yuan et al.
Tensor-train density estimation
Georgii S. Novikov, Maxim E. Panov, Ivan V. Oseledets