Papers
11,015 papers found
MAML is a Noisy Contrastive Learner in Classification
Chia Hsiang Kao, Wei-Chen Chiu, Pin-Yu Chen
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments
Sugandha Sharma, Aidan Curtis, Marta Kryven et al.
Mapping conditional distributions for domain adaptation under generalized target shift
Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bezenac et al.
Mapping Language Models to Grounded Conceptual Spaces
Roma Patel, Ellie Pavlick
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
Denis Yarats, Rob Fergus, Alessandro Lazaric et al.
Maximizing Ensemble Diversity in Deep Reinforcement Learning
Hassam Sheikh, Mariano Phielipp, Ladislau Boloni
Maximum Entropy RL (Provably) Solves Some Robust RL Problems
Benjamin Eysenbach, Sergey Levine
Maximum n-times Coverage for Vaccine Design
Ge Liu, Alexander Dimitrakakis, Brandon Carter et al.
MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC
Erik Nijkamp, Ruiqi Gao, Pavel Sountsov et al.
Measuring CLEVRness: Black-box Testing of Visual Reasoning Models
Spyridon Mouselinos, Henryk Michalewski, Mateusz Malinowski
Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing
Iro Laina, Yuki M Asano, Andrea Vedaldi
Memorizing Transformers
Yuhuai Wu, Markus Norman Rabe, DeLesley Hutchins et al.
Memory Augmented Optimizers for Deep Learning
Paul-Aymeric Martin McRae, Prasanna Parthasarathi, Mido Assran et al.
Memory Replay with Data Compression for Continual Learning
Liyuan Wang, Xingxing Zhang, Kuo Yang et al.
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald et al.
Message Passing Neural PDE Solvers
Johannes Brandstetter, Daniel E. Worrall, Max Welling
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data
Haoang Chi, Feng Liu, Wenjing Yang et al.
Meta-Imitation Learning by Watching Video Demonstrations
Jiayi Li, Tao Lu, Xiaoge Cao et al.
Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty
Jeffrey Ryan Willette, Hae Beom Lee, Juho Lee et al.
Meta-Learning with Fewer Tasks through Task Interpolation
Huaxiu Yao, Linjun Zhang, Chelsea Finn
MetaMorph: Learning Universal Controllers with Transformers
Agrim Gupta, Linxi Fan, Surya Ganguli et al.
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling
Yusong Wu, Ethan Manilow, Yi Deng et al.
Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks
Peihao Zhu, Rameen Abdal, John Femiani et al.
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond
Chulhee Yun, Shashank Rajput, Suvrit Sra