Papers
11,015 papers found
Neural gradients are near-lognormal: improved quantized and sparse training
Brian Chmiel, Liad Ben-Uri, Moran Shkolnik et al.
Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering
Calypso Herrera, Florian Krach, Josef Teichmann
Neural Learning of One-of-Many Solutions for Combinatorial Problems in Structured Output Spaces
Yatin Nandwani, Deepanshu Jindal, Mausam . et al.
Neurally Augmented ALISTA
Freya Behrens, Jonathan Sauder, Peter Jung
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics
Daniel Kunin, Javier Sagastuy-Brena, Surya Ganguli et al.
Neural Networks for Learning Counterfactual G-Invariances from Single Environments
S Chandra Mouli, Bruno Ribeiro
Neural networks with late-phase weights
Johannes von Oswald, Seijin Kobayashi, Joao Sacramento et al.
Neural ODE Processes
Alexander Norcliffe, Cristian Bodnar, Ben Day et al.
Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang et al.
Neural representation and generation for RNA secondary structures
Zichao Yan, William L. Hamilton, Mathieu Blanchette
Neural Spatio-Temporal Point Processes
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
Neural Synthesis of Binaural Speech From Mono Audio
Alexander Richard, Dejan Markovic, Israel D. Gebru et al.
Neural Thompson Sampling
Weitong ZHANG, Dongruo Zhou, Lihong Li et al.
Neural Topic Model via Optimal Transport
He Zhao, Dinh Phung, Viet Huynh et al.
New Bounds For Distributed Mean Estimation and Variance Reduction
Peter Davies, Vijaykrishna Gurunanthan, Niusha Moshrefi et al.
No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania et al.
Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye et al.
Noise or Signal: The Role of Image Backgrounds in Object Recognition
Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas et al.
No MCMC for me: Amortized sampling for fast and stable training of energy-based models
Will Sussman Grathwohl, Jacob Jin Kelly, Milad Hashemi et al.
Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds
Yihao Feng, Ziyang Tang, na zhang et al.
Nonseparable Symplectic Neural Networks
Shiying Xiong, Yunjin Tong, Xingzhe He et al.
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control
Ioannis Exarchos, Marcus Aloysius Pereira, Ziyi Wang et al.
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa et al.
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation
Justin Fu, Sergey Levine