Bietti, Alberto

46 publications

NeurIPS 2025 AION-1: Omnimodal Foundation Model for Astronomical Sciences Liam Holden Parker, Francois Lanusse, Jeff Shen, Ollie Liu, Tom Hehir, Leopoldo Sarra, Lucas Thibaut Meyer, Micah Bowles, Sebastian Wagner-Carena, Helen Qu, Siavash Golkar, Alberto Bietti, Hatim Bourfoune, Pierre Cornette, Keiya Hirashima, Geraud Krawezik, Ruben Ohana, Nicholas Lourie, Michael McCabe, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Kyunghyun Cho, Miles Cranmer, Shirley Ho
ICML 2025 BAnG: Bidirectional Anchored Generation for Conditional RNA Design Roman Klypa, Alberto Bietti, Sergei Grudinin
TMLR 2025 Counterfactual Learning of Stochastic Policies with Continuous Actions Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Pierre Gaillard, Julien Mairal
ICLR 2025 Distributional Associations vs In-Context Reasoning: A Study of Feed-Forward and Attention Layers Lei Chen, Joan Bruna, Alberto Bietti
NeurIPS 2025 Emergence of Linear Truth Encodings in Language Models Shauli Ravfogel, Gilad Yehudai, Tal Linzen, Joan Bruna, Alberto Bietti
NeurIPS 2025 From Shortcut to Induction Head: How Data Diversity Shapes Algorithm Selection in Transformers Ryotaro Kawata, Yujin Song, Alberto Bietti, Naoki Nishikawa, Taiji Suzuki, Samuel Vaiter, Denny Wu
ICML 2025 In-Context Denoising with One-Layer Transformers: Connections Between Attention and Associative Memory Retrieval Matthew Smart, Alberto Bietti, Anirvan M. Sengupta
ICLRW 2025 In-Context Denoising with One-Layer Transformers: Connections Between Attention and Associative Memory Retrieval Matthew Smart, Alberto Bietti, Anirvan M. Sengupta
COLT 2025 Learning Compositional Functions with Transformers from Easy-to-Hard Data Zixuan Wang, Eshaan Nichani, Alberto Bietti, Alex Damian, Daniel Hsu, Jason D Lee, Denny Wu
AISTATS 2025 Level Set Teleportation: An Optimization Perspective Aaron Mishkin, Alberto Bietti, Robert M. Gower
NeurIPS 2025 Predicting Partially Observable Dynamical Systems via Diffusion Models with a Multiscale Inference Scheme Rudy Morel, Francesco Pio Ramunno, Jeff Shen, Alberto Bietti, Kyunghyun Cho, Miles Cranmer, Siavash Golkar, Olexandr Gugnin, Geraud Krawezik, Tanya Marwah, Michael McCabe, Lucas Thibaut Meyer, Payel Mukhopadhyay, Ruben Ohana, Liam Holden Parker, Helen Qu, François Rozet, K.D. Leka, Francois Lanusse, David Fouhey, Shirley Ho
ICLR 2025 Understanding Factual Recall in Transformers via Associative Memories Eshaan Nichani, Jason D. Lee, Alberto Bietti
NeurIPS 2024 Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models Frederik Kunstner, Alan Milligan, Robin Yadav, Mark Schmidt, Alberto Bietti
NeurIPSW 2024 Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models Frederik Kunstner, Alan Milligan, Robin Yadav, Mark Schmidt, Alberto Bietti
ICMLW 2024 How Truncating Weights Improves Reasoning in Language Models Lei Chen, Joan Bruna, Alberto Bietti
ICMLW 2024 How Truncating Weights Improves Reasoning in Language Models Lei Chen, Joan Bruna, Alberto Bietti
ICML 2024 Learning Associative Memories with Gradient Descent Vivien Cabannes, Berfin Simsek, Alberto Bietti
NeurIPS 2024 Multiple Physics Pretraining for Spatiotemporal Surrogate Models Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Parker, Ruben Ohana, Miles Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Geraud Krawezik, Francois Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho
ICLR 2024 Scaling Laws for Associative Memories Vivien Cabannes, Elvis Dohmatob, Alberto Bietti
NeurIPSW 2024 Understanding Factual Recall in Transformers via Associative Memories Eshaan Nichani, Jason D. Lee, Alberto Bietti
NeurIPSW 2023 Associative Memories with Heavy-Tailed Data Vivien Cabannes, Elvis Dohmatob, Alberto Bietti
NeurIPSW 2023 Associative Memories with Heavy-Tailed Data Vivien Cabannes, Elvis Dohmatob, Alberto Bietti
NeurIPSW 2023 AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models Francois Lanusse, Liam Holden Parker, Siavash Golkar, Alberto Bietti, Miles Cranmer, Michael Eickenberg, Geraud Krawezik, Michael McCabe, Ruben Ohana, Mariel Pettee, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho
NeurIPS 2023 Birth of a Transformer: A Memory Viewpoint Alberto Bietti, Vivien Cabannes, Diane Bouchacourt, Herve Jegou, Leon Bottou
NeurIPSW 2023 Level Set Teleportation: The Good, the Bad, and the Ugly Aaron Mishkin, Alberto Bietti, Robert M. Gower
NeurIPSW 2023 Multiple Physics Pretraining for Physical Surrogate Models Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Geraud Krawezik, Francois Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho
ICML 2023 The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann Lecun, Alberto Bietti
ICLRW 2023 The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
NeurIPSW 2023 Why Adam Outperforms Gradient Descent on Language Models: A Heavy-Tailed Class Imbalance Problem Robin Yadav, Frederik Kunstner, Mark Schmidt, Alberto Bietti
NeurIPSW 2023 xVal: A Continuous Number Encoding for Large Language Models Siavash Golkar, Mariel Pettee, Michael Eickenberg, Alberto Bietti, Miles Cranmer, Geraud Krawezik, Francois Lanusse, Michael McCabe, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho
AISTATS 2022 Efficient Kernelized UCB for Contextual Bandits Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard
ICLR 2022 Approximation and Learning with Deep Convolutional Models: A Kernel Perspective Alberto Bietti
NeurIPS 2022 Learning Single-Index Models with Shallow Neural Networks Alberto Bietti, Joan Bruna, Clayton Sanford, Min Jae Song
ICML 2022 Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning Alberto Bietti, Chen-Yu Wei, Miroslav Dudik, John Langford, Steven Wu
NeurIPS 2022 When Does Return-Conditioned Supervised Learning Work for Offline Reinforcement Learning? David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
JMLR 2021 A Contextual Bandit Bake-Off Alberto Bietti, Alekh Agarwal, John Langford
ICLR 2021 Deep Equals Shallow for ReLU Networks in Kernel Regimes Alberto Bietti, Francis Bach
ICML 2021 On Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna
NeurIPS 2021 On the Sample Complexity of Learning Under Geometric Stability Alberto Bietti, Luca Venturi, Joan Bruna
NeurIPS 2021 On the Universality of Graph Neural Networks on Large Random Graphs Nicolas Keriven, Alberto Bietti, Samuel Vaiter
NeurIPS 2020 Convergence and Stability of Graph Convolutional Networks on Large Random Graphs Nicolas Keriven, Alberto Bietti, Samuel Vaiter
ICML 2019 A Kernel Perspective for Regularizing Deep Neural Networks Alberto Bietti, Grégoire Mialon, Dexiong Chen, Julien Mairal
JMLR 2019 Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional Representations Alberto Bietti, Julien Mairal
NeurIPS 2019 On the Inductive Bias of Neural Tangent Kernels Alberto Bietti, Julien Mairal
NeurIPS 2017 Invariance and Stability of Deep Convolutional Representations Alberto Bietti, Julien Mairal
NeurIPS 2017 Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure Alberto Bietti, Julien Mairal