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Meta-Learning Black-Box Optimization via Black-Box Optimization
Robert Lange, Tom Schaul, Tom Zahavy, Yutian Chen, Valentin Dalibard, Chris Lu, Satinder Baveja, Sebastian Flennerhag
ICLR
2023-05-01
Meta-Learning
Self-supervised learning
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Is forgetting less a good inductive bias for forward transfer?
Arslan Chaudhry, Jiefeng Chen, Timothy Nguyen, Dilan Gorur
ICLR
2023-05-01
Continual & transfer learning
Deep learning
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Fast exploration and learning of latent graphs with aliased observations
Miguel Lazaro-Gredilla, Ishan Deshpande, Siva Swaminathan, Meet Dave, Dileep George
arXiv
2023-03-13
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Denoising diffusion samplers
Francisco Vargas, Will Grathwohl, Arnaud Doucet
ICLR
2023-02-28
Probabilistic learning
Simulations
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Graph schemas as abstractions for transfer learning, inference, and planning
Swaroop Guntupalli, Rajkumar Vasudeva Raju, Shrinu Kushagra, Carter Wendelken, Danny Sawyer, Ishan Deshpande, Stannis Zhou, Miguel Lazaro-Gredilla, Dileep George
arXiv
2023-02-16
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Universal Agent Mixtures and the Geometry of Intelligence
Samuel Allen Alexander *, David Quarel *, Len Du *, Marcus Hutter
AISTATS
2023-02-13
Reinforcement learning
Theory & foundations
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Equivariant MuZero
Andreea Deac *, Theophane Weber, George Papamakarios
arXiv
2023-02-09
Deep reinforcement learning
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Scaling Goal-based Exploration via Pruning Proto-goals
Akhil Bagaria *, Ray Jiang, Ramana Kumar, Tom Schaul
arXiv
2023-02-09
Reinforcement learning
Deep reinforcement learning
Continual & transfer learning
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3D Neural Embedding Likelihood for Robust Sim-to-Real Transfer in Inverse Graphics
Stannis Zhou, Nishad Gothoskar *, Lirui Wang *, Josh Tenenbaum *, Dan Gutfreund *, Miguel Lazaro-Gredilla, Dileep George, Vikash Mansinghka *
arXiv
2023-02-07
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Exploration via Epistemic Value Estimation
Simon Schmitt, John Shawe-Taylor *, Hado van Hasselt
AAAI
2023-02-07
Deep reinforcement learning
Reinforcement learning
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Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation
Antoine Dedieu, Stannis Zhou, Dileep George, Miguel Lazaro-Gredilla
arXiv
2023-02-02
Probabilistic learning
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Dual Algorithmic Reasoning
Danilo Numeroso *, Davide Bacciu *, Petar Veličković
ICLR
2023-02-02
Relational reasoning
Neural programming
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Reinforcement Learning for Minimizing Age of Information over Wireless Links
Elif Tugce Ceran *, Deniz Gündüz *, Andras Gyorgy
Age of Information: Foundations and Applications
2023-02-02
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Distilling Internet-Scale Vision-Language Models into Embodied Agents
Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta, Theodore Sumers *
arXiv
2023-01-29
Language
Vision
Reinforcement learning
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Pragmatic Fairness: Developing Policies with Outcome Disparity Control
Silvia Chiappa, Alan Malek, Ricardo Silva *, Siyuan Guo *
arXiv
2023-01-28
Causal inference
Fairness
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On a continuous time model of gradient descent dynamics and instability in deep learning
Mihaela Rosca, Yan Wu, Chongli Qin, Benoit Dherin *
Transactions on Machine Learning Research (TMLR)
2023-01-25
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Discovering Quantum Phase Transitions with Fermionic Neural Networks
Gino Cassella *, Halvard Sutterud *, Matthew Foulkes *, David Pfau, Neil Drummond *, Sam Azadi *, James Spencer
Physical Review Letters
2023-01-20
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Transformer Grammars: Augmenting Transformer Language Models with a Syntactic Inductive Bias
Laurent Sartran, Samuel Barrett *, Adhi Kuncoro, Miloš Stanojević, Phil Blunsom *, Chris Dyer
Transactions of the Association for Computational Linguistics (TACL)
2022-12-22
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Confident Approximate Policy Iteration for Efficient Local Planning in q^π-realizable MDPs
Andras Gyorgy, Csaba Szepesvari, Tadashi Kozuno *, Gellért Weisz
NeurIPS
2022-12-16
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Particle-Based Score Estimation for Jointly Learning Transition and Observation Models in Autonomous Driving
Angad Singh *, Omar Makhlouf *, Maximilian Igl *, Joao Messias *, Arnaud Doucet, Shimon Whiteson *
CoRL
2022-12-14
Probabilistic learning
Control & robotics
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ipie: A Python-based Auxiliary-Field Quantum Monte Carlo Program with Flexibility and Efficiency on CPUs and GPUs
Fionn Malone *, Ankit Mahajan *, James Spencer, Joonho Lee *
Journal of Chemical Theory and Computation
2022-12-12
Code
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Score-based generative models learn manifold-like structures with constrained mixing
Kevin Li, Ben Moran
NeurIPS Workshop
2022-12-10
Unsupervised learning & generative models
Safety
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Reasoning-Modulated Representations
Petar Veličković, Matko Bošnjak, Thomas Kipf *, Alexander Lerchner, Raia Hadsell, Razvan Pascanu, Charles Blundell
LoG
2022-12-09
Representation learning
Self-supervised learning
Relational reasoning
Neural programming
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Learning Graph Search Heuristics
Michal Pándy *, Weikang Qiu *, Gabriele Corso *, Petar Veličković, Rex Ying *, Jure Leskovec *, Pietro Liò *
LoG
2022-12-09
Planning
Relational reasoning
Neural programming
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Continuous Neural Algorithmic Planners
Yu He *, Petar Veličković, Pietro Liò *, Andreea-Ioana Deac
LoG
2022-12-09
Deep reinforcement learning
Planning
Relational reasoning
Neural programming
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