Achille, Alessandro

39 publications

TMLR 2025 LC-PLM: Long-Context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers Yingheng Wang, Zichen Wang, Gil Sadeh, Luca Zancato, Alessandro Achille, George Karypis, Huzefa Rangwala

ICLR 2025 PICASO: Permutation-Invariant Context Composition with State Space Models Tian Yu Liu, Alessandro Achille, Matthew Trager, Aditya Golatkar, Luca Zancato, Stefano Soatto

NeurIPS 2024 B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory Luca Zancato, Arjun Seshadri, Yonatan Dukler, Aditya Golatkar, Yantao Shen, Benjamin Bowman, Matthew Trager, Alessandro Achille, Stefano Soatto

CVPR 2024 CPR: Retrieval Augmented Generation for Copyright Protection Aditya Golatkar, Alessandro Achille, Luca Zancato, Yu-Xiang Wang, Ashwin Swaminathan, Stefano Soatto

ICLR 2024 Critical Learning Periods Emerge Even in Deep Linear Networks Michael Kleinman, Alessandro Achille, Stefano Soatto

ECCV 2024 Diffusion Soup: Model Merging for Text-to-Image Diffusion Models Benjamin J Biggs, Arjun Seshadri, Yang Zou, Achin Jain, Aditya Golatkar, Yusheng Xie, Alessandro Achille, Ashwin Swaminathan, Stefano Soatto

CVPR 2024 Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding Alessandro Achille, Greg Ver Steeg, Tian Yu Liu, Matthew Trager, Carson Klingenberg, Stefano Soatto

ICLR 2024 Meaning Representations from Trajectories in Autoregressive Models Tian Yu Liu, Matthew Trager, Alessandro Achille, Pramuditha Perera, Luca Zancato, Stefano Soatto

CVPR 2024 Multi-Modal Hallucination Control by Visual Information Grounding Alessandro Favero, Luca Zancato, Matthew Trager, Siddharth Choudhary, Pramuditha Perera, Alessandro Achille, Ashwin Swaminathan, Stefano Soatto

CVPR 2023 A Meta-Learning Approach to Predicting Performance and Data Requirements Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele, Ashwin Swaminathan, Stefano Soatto

CVPR 2023 A-La-Carte Prompt Tuning (APT): Combining Distinct Data via Composable Prompting Benjamin Bowman, Alessandro Achille, Luca Zancato, Matthew Trager, Pramuditha Perera, Giovanni Paolini, Stefano Soatto

CVPR 2023 Critical Learning Periods for Multisensory Integration in Deep Networks Michael Kleinman, Alessandro Achille, Stefano Soatto

NeurIPS 2023 Gacs-Korner Common Information Variational Autoencoder Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan Kao

NeurIPS 2023 Leveraging Sparse and Shared Feature Activations for Disentangled Representation Learning Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello

ICCV 2023 Linear Spaces of Meanings: Compositional Structures in Vision-Language Models Matthew Trager, Pramuditha Perera, Luca Zancato, Alessandro Achille, Parminder Bhatia, Stefano Soatto

ICCV 2023 SAFE: Machine Unlearning with Shard Graphs Yonatan Dukler, Benjamin Bowman, Alessandro Achille, Aditya Golatkar, Ashwin Swaminathan, Stefano Soatto

CVPR 2023 Train/Test-Time Adaptation with Retrieval Luca Zancato, Alessandro Achille, Tian Yu Liu, Matthew Trager, Pramuditha Perera, Stefano Soatto

NeurIPS 2023 Your Representations Are in the Network: Composable and Parallel Adaptation for Large Scale Models Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Benjamin Bowman, Avinash Ravichandran, Charless C. Fowlkes, Ashwin Swaminathan, Stefano Soatto

ICLR 2022 DIVA: Dataset Derivative of a Learning Task Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto

CVPR 2022 Mixed Differential Privacy in Computer Vision Aditya Golatkar, Alessandro Achille, Yu-Xiang Wang, Aaron Roth, Michael Kearns, Stefano Soatto

NeurIPS 2022 On Leave-One-Out Conditional Mutual Information for Generalization Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas Diggavi, Stefano Soatto

CVPR 2022 Task Adaptive Parameter Sharing for Multi-Task Learning Matthew Wallingford, Hao Li, Alessandro Achille, Avinash Ravichandran, Charless Fowlkes, Rahul Bhotika, Stefano Soatto

AAAI 2021 Adversarial Training Reduces Information and Improves Transferability Matteo Terzi, Alessandro Achille, Marco Maggipinto, Gian Antonio Susto

ICLR 2021 Estimating Informativeness of Samples with Smooth Unique Information Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

CVPR 2021 LQF: Linear Quadratic Fine-Tuning Alessandro Achille, Aditya Golatkar, Avinash Ravichandran, Marzia Polito, Stefano Soatto

ICCV 2021 LayoutTransformer: Layout Generation and Completion with Self-Attention Kamal Gupta, Justin Lazarow, Alessandro Achille, Larry S. Davis, Vijay Mahadevan, Abhinav Shrivastava

CVPR 2021 Mixed-Privacy Forgetting in Deep Networks Aditya Golatkar, Alessandro Achille, Avinash Ravichandran, Marzia Polito, Stefano Soatto

NeurIPS 2021 On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning Julian Zilly, Alessandro Achille, Andrea Censi, Emilio Frazzoli

ICLRW 2021 Redundant Information Neural Estimation Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan Kao

ICLR 2021 Structured Prediction as Translation Between Augmented Natural Languages Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cicero Nogueira dos Santos, Bing Xiang, Stefano Soatto

ICLR 2021 Usable Information and Evolution of Optimal Representations During Training Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan Kao

ECCV 2020 Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations Aditya Golatkar, Alessandro Achille, Stefano Soatto

ECCV 2020 Incremental Few-Shot Meta-Learning via Indirect Discriminant Alignment Qing Liu, Orchid Majumder, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

NeurIPS 2020 Predicting Training Time Without Training Luca Zancato, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

NeurIPSW 2020 Usable Information and Evolution of Optimal Representations During Training Michael Kleinman, Daksh Idnani, Alessandro Achille, Jonathan Kao

ICLR 2019 Critical Learning Periods in Deep Networks Alessandro Achille, Matteo Rovere, Stefano Soatto

NeurIPS 2019 Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little near Convergence Aditya Sharad Golatkar, Alessandro Achille, Stefano Soatto

JMLR 2018 Emergence of Invariance and Disentanglement in Deep Representations Alessandro Achille, Stefano Soatto

NeurIPS 2018 Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies Alessandro Achille, Tom Eccles, Loic Matthey, Chris Burgess, Nicholas Watters, Alexander Lerchner, Irina Higgins