Papers
11,951 papers found
MT3: Multi-Task Multitrack Music Transcription
Joshua P Gardner, Ian Simon, Ethan Manilow et al.
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction
Jorge Quesada, Lakshmi Sathidevi, Ran Liu et al.
Multi-Agent Learning for Iterative Dominance Elimination: Formal Barriers and New Algorithms
Jibang Wu, Haifeng Xu, Fan Yao
Multi-Agent MDP Homomorphic Networks
Elise van der Pol, Herke van Hoof, Frans A Oliehoek et al.
Multi-Critic Actor Learning: Teaching RL Policies to Act with Style
Siddharth Mysore, George Cheng, Yunqi Zhao et al.
Multimeasurement Generative Models
Saeed Saremi, Rupesh Kumar Srivastava
Multi-objective Optimization by Learning Space Partition
Yiyang Zhao, Linnan Wang, Kevin Yang et al.
Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation
Yan Zhang, David W Zhang, Simon Lacoste-Julien et al.
Multi-Stage Episodic Control for Strategic Exploration in Text Games
Jens Tuyls, Shunyu Yao, Sham M. Kakade et al.
Multi-Task Processes
Donggyun Kim, Seongwoong Cho, Wonkwang Lee et al.
Multitask Prompted Training Enables Zero-Shot Task Generalization
Victor Sanh, Albert Webson, Colin Raffel et al.
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy
Yash Mehta, Colin White, Arber Zela et al.
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization
Yao Shu, Shaofeng Cai, Zhongxiang Dai et al.
NASPY: Automated Extraction of Automated Machine Learning Models
Xiaoxuan Lou, Shangwei Guo, Jiwei Li et al.
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training
Chengyue Gong, Dilin Wang, Meng Li et al.
Natural Language Descriptions of Deep Visual Features
Evan Hernandez, Sarah Schwettmann, David Bau et al.
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions
Bertrand Charpentier, Oliver Borchert, Daniel Zügner et al.
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Ming Yin, Yaqi Duan, Mengdi Wang et al.
Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver
Xiaoyu Chen, Jiachen Hu, Lin Yang et al.
Network Augmentation for Tiny Deep Learning
Han Cai, Chuang Gan, Ji Lin et al.
NETWORK INSENSITIVITY TO PARAMETER NOISE VIA PARAMETER ATTACK DURING TRAINING
Julian Büchel, Fynn Firouz Faber, Dylan Richard Muir
NeuPL: Neural Population Learning
Siqi Liu, Luke Marris, Daniel Hennes et al.
Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path
X.Y. Han, Vardan Papyan, David L. Donoho
Neural Contextual Bandits with Deep Representation and Shallow Exploration
Pan Xu, Zheng Wen, Handong Zhao et al.