Papers
8,340 papers found
Metagenomic Binning using Connectivity-constrained Variational Autoencoders
Andre Lamurias, Alessandro Tibo, Katja Hose et al.
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks
Shibo Li, Michael Penwarden, Yiming Xu et al.
Meta-learning Parameterized Skills
Haotian Fu, Shangqun Yu, Saket Tiwari et al.
Meta-Learning the Inductive Bias of Simple Neural Circuits
Will Dorrell, Maria Yuffa, Peter E. Latham
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks
Wenfang Sun, Yingjun Du, Xiantong Zhen et al.
Meta Optimal Transport
Brandon Amos, Giulia Luise, Samuel Cohen et al.
Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization
Jiwoo Son, Minsu Kim, Hyeonah Kim et al.
MetricGAN-OKD: Multi-Metric Optimization of MetricGAN via Online Knowledge Distillation for Speech Enhancement
Wooseok Shin, Byung Hoon Lee, Jin Sob Kim et al.
MEWL: Few-shot multimodal word learning with referential uncertainty
Guangyuan Jiang, Manjie Xu, Shiji Xin et al.
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods
Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman et al.
Mimetic Initialization of Self-Attention Layers
Asher Trockman, J Zico Kolter
Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints
Alexandra Anna Lassota, Alexander Lindermayr, Nicole Megow et al.
Minimax estimation of discontinuous optimal transport maps: The semi-discrete case
Aram-Alexandre Pooladian, Vincent Divol, Jonathan Niles-Weed
Minimizing Trajectory Curvature of ODE-based Generative Models
Sangyun Lee, Beomsu Kim, Jong Chul Ye
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation
Li’Ang Li, Yifei Duan, Guanghua Ji et al.
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes
Marin Ballu, Quentin Berthet
Mitigating Memorization of Noisy Labels by Clipping the Model Prediction
Hongxin Wei, Huiping Zhuang, Renchunzi Xie et al.
Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling
Arka Daw, Jie Bu, Sifan Wang et al.
Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning
Yu Yang, Besmira Nushi, Hamid Palangi et al.
MixFlows: principled variational inference via mixed flows
Zuheng Xu, Naitong Chen, Trevor Campbell
Mixing Predictions for Online Metric Algorithms
Antonios Antoniadis, Christian Coester, Marek Elias et al.
Mixture Proportion Estimation Beyond Irreducibility
Yilun Zhu, Aaron Fjeldsted, Darren Holland et al.
Moccasin: Efficient Tensor Rematerialization for Neural Networks
Burak Bartan, Haoming Li, Harris Teague et al.
Modality-Agnostic Variational Compression of Implicit Neural Representations
Jonathan Richard Schwarz, Jihoon Tack, Yee Whye Teh et al.
Model-agnostic Measure of Generalization Difficulty
Akhilan Boopathy, Kevin Liu, Jaedong Hwang et al.