Information Dropout: learning optimal representations through noise. - Alessandro Achille; Stefano Soatto (CoRR, 2016)

On the Emergence of Invariance and Disentangling in Deep Representations. - Alessandro Achille; Stefano Soatto (CoRR, 2017)

Critical Learning Periods in Deep Neural Networks. - Alessandro Achille; Matteo Rovere; Stefano Soatto (CoRR, 2017)

Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies. - Alessandro Achille; Tom Eccles; Loïc Matthey; Christopher P. Burgess; Nicholas Watters; Alexander Lerchner; Irina Higgins (NeurIPS, 2018)

A Separation Principle for Control in the Age of Deep Learning. - Alessandro Achille; Stefano Soatto (Annu. Rev. Control. Robotics Auton. Syst., 2018)

The Dynamics of Differential Learning I: Information-Dynamics and Task Reachability. - Alessandro Achille; Glen Mbeng; Stefano Soatto (CoRR, 2018)

Emergence of Invariance and Disentanglement in Deep Representations. - Alessandro Achille; Stefano Soatto (J. Mach. Learn. Res., 2018)

Information Dropout: Learning Optimal Representations Through Noisy Computation. - Alessandro Achille; Stefano Soatto (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Task2Vec: Task Embedding for Meta-Learning. - Alessandro Achille; Michael Lam; Rahul Tewari; Avinash Ravichandran; Subhransu Maji; Charless C. Fowlkes; Stefano Soatto; Pietro Perona (ICCV, 2019)

Critical Learning Periods in Deep Networks. - Alessandro Achille; Matteo Rovere; Stefano Soatto (ICLR (Poster), 2019)

Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence. - Aditya Golatkar; Alessandro Achille; Stefano Soatto (NeurIPS, 2019)

The Information Complexity of Learning Tasks, their Structure and their Distance. - Alessandro Achille; Giovanni Paolini; Glen Mbeng; Stefano Soatto (CoRR, 2019)

Where is the Information in a Deep Neural Network? - Alessandro Achille; Stefano Soatto (CoRR, 2019)

Toward Understanding Catastrophic Forgetting in Continual Learning. - Cuong V. Nguyen; Alessandro Achille; Michael Lam; Tal Hassner; Vijay Mahadevan; Stefano Soatto (CoRR, 2019)

TextTubes for Detecting Curved Text in the Wild. - Joël Seytre; Jon Wu; Alessandro Achille (CoRR, 2019)

Emergent Properties of Deep Neural Networks. - Alessandro Achille (2019)

Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks. - Aditya Golatkar; Alessandro Achille; Stefano Soatto (CVPR, 2020)

Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations. - Aditya Golatkar; Alessandro Achille; Stefano Soatto (ECCV (29), 2020)

Incremental Few-Shot Meta-learning via Indirect Discriminant Alignment. - Qing Liu; Orchid Majumder; Alessandro Achille; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ECCV (7), 2020)

Predicting Training Time Without Training. - Luca Zancato; Alessandro Achille; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (NeurIPS, 2020)

Layout Generation and Completion with Self-attention. - Kamal Gupta 002; Alessandro Achille; Justin Lazarow; Larry Davis 001; Vijay Mahadevan; Abhinav Shrivastava (CoRR, 2020)

Adversarial Training Reduces Information and Improves Transferability. - Matteo Terzi; Alessandro Achille; Marco Maggipinto; Gian Antonio Susto (AAAI, 2021)

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

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

LayoutTransformer: Layout Generation and Completion with Self-attention. - Kamal Gupta 002; Justin Lazarow; Alessandro Achille; Larry Davis 001; Vijay Mahadevan; Abhinav Shrivastava (ICCV, 2021)

Estimating informativeness of samples with Smooth Unique Information. - Hrayr Harutyunyan; Alessandro Achille; Giovanni Paolini; Orchid Majumder; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ICLR, 2021)

Usable Information and Evolution of Optimal Representations During Training. - Michael Kleinman; Alessandro Achille; Daksh Idnani; Jonathan C. Kao (ICLR, 2021)

Structured Prediction as Translation between Augmented Natural Languages. - Giovanni Paolini; Ben Athiwaratkun; Jason Krone; Jie Ma; Alessandro Achille; Rishita Anubhai; Cícero Nogueira dos Santos; Bing Xiang; Stefano Soatto (ICLR, 2021)

On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning. - Julian G. Zilly; Alessandro Achille; Andrea Censi; Emilio Frazzoli (NeurIPS, 2021)

A linearized framework and a new benchmark for model selection for fine-tuning. - Aditya Deshpande; Alessandro Achille; Avinash Ravichandran; Hao Li; Luca Zancato; Charless C. Fowlkes; Rahul Bhotika; Stefano Soatto; Pietro Perona (CoRR, 2021)

Redundant Information Neural Estimation. - Michael Kleinman; Alessandro Achille; Stefano Soatto; Jonathan C. Kao (Entropy, 2021)

Mixed Differential Privacy in Computer Vision. - Aditya Golatkar; Alessandro Achille; Yu-Xiang Wang 003; Aaron Roth 001; Michael Kearns; Stefano Soatto (CVPR, 2022)

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

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

On Leave-One-Out Conditional Mutual Information For Generalization. - Mohamad Rida Rammal; Alessandro Achille; Aditya Golatkar; Suhas N. Diggavi; Stefano Soatto (NeurIPS, 2022)

Stacked Residuals of Dynamic Layers for Time Series Anomaly Detection. - Luca Zancato; Alessandro Achille; Giovanni Paolini; Alessandro Chiuso; Stefano Soatto (CoRR, 2022)

Towards Differential Relational Privacy and its use in Question Answering. - Simone Bombari; Alessandro Achille; Zijian Wang 002; Yu-Xiang Wang 003; Yusheng Xie; Kunwar Yashraj Singh; Srikar Appalaraju; Vijay Mahadevan; Stefano Soatto (CoRR, 2022)

On Binding Objects to Symbols: Learning Physical Concepts to Understand Real from Fake. - Alessandro Achille; Stefano Soatto (CoRR, 2022)

Integral Continual Learning Along the Tangent Vector Field of Tasks. - Tian Yu Liu; Aditya Golatkar; Stefano Soatto; Alessandro Achille (CoRR, 2022)

À-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)

A Meta-Learning Approach to Predicting Performance and Data Requirements. - Achin Jain; Gurumurthy Swaminathan; Paolo Favaro; Hao Yang 043; Avinash Ravichandran; Hrayr Harutyunyan; Alessandro Achille; Onkar Dabeer; Bernt Schiele; Ashwin Swaminathan; Stefano Soatto (CVPR, 2023)

Critical Learning Periods for Multisensory Integration in Deep Networks. - Michael Kleinman; Alessandro Achille; Stefano Soatto (CVPR, 2023)

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

SAFE: Machine Unlearning With Shard Graphs. - Yonatan Dukler; Benjamin Bowman; Alessandro Achille; Aditya Golatkar; Ashwin Swaminathan; Stefano Soatto (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)

Your representations are in the network: composable and parallel adaptation for large scale models. - Yonatan Dukler; Alessandro Achille; Hao Yang 043; Varsha Vivek; Luca Zancato; Benjamin Bowman; Avinash Ravichandran; Charless C. Fowlkes; Ashwin Swaminathan; Stefano Soatto (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 (NeurIPS, 2023)

Gacs-Korner Common Information Variational Autoencoder. - Michael Kleinman; Alessandro Achille; Stefano Soatto; Jonathan C. Kao (NeurIPS, 2023)

Linear Spaces of Meanings: the Compositional Language of VLMs. - Matthew Trager; Pramuditha Perera; Luca Zancato; Alessandro Achille; Parminder Bhatia; Bing Xiang; Stefano Soatto (CoRR, 2023)

Introspective Cross-Attention Probing for Lightweight Transfer of Pre-trained Models. - Yonatan Dukler; Alessandro Achille; Hao Yang 043; Varsha Vivek; Luca Zancato; Benjamin Bowman; Avinash Ravichandran; Charless C. Fowlkes; Ashwin Swaminathan; Stefano Soatto (CoRR, 2023)

AI Model Disgorgement: Methods and Choices. - Alessandro Achille; Michael Kearns; Carson Klingenberg; Stefano Soatto (CoRR, 2023)

Prompt Algebra for Task Composition. - Pramuditha Perera; Matthew Trager; Luca Zancato; Alessandro Achille; Stefano Soatto (CoRR, 2023)

Towards Visual Foundational Models of Physical Scenes. - Chethan Parameshwara; Alessandro Achille; Matthew Trager; Xiaolong Li; Jiawei Mo; Ashwin Swaminathan; CJ Taylor; Dheera Venkatraman; Xiaohan Fei; Stefano Soatto (CoRR, 2023)

Training Data Protection with Compositional Diffusion Models. - Aditya Golatkar; Alessandro Achille; Ashwin Swaminathan; Stefano Soatto (CoRR, 2023)

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 (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, 2024)

CPR: Retrieval Augmented Generation for Copyright Protection. - Aditya Golatkar; Alessandro Achille; Luca Zancato; Yu-Xiang Wang 003; Ashwin Swaminathan; Stefano Soatto (CVPR, 2024)

Diffusion Soup: Model Merging for Text-to-Image Diffusion Models. - Benjamin Biggs; Arjun Seshadri; Yang Zou; Achin Jain; Aditya Golatkar; Yusheng Xie; Alessandro Achille; Ashwin Swaminathan; Stefano Soatto (ECCV (63), 2024)

Snakes and Ladders: Accelerating SSM Inference with Speculative Decoding. - Yangchao Wu; Yonatan Dukler; Matthew Trager; Alessandro Achille; Wei Xia; Stefano Soatto (ENLSP, 2024)

Critical Learning Periods Emerge Even in Deep Linear Networks. - Michael Kleinman; Alessandro Achille; Stefano Soatto (ICLR, 2024)

Meaning Representations from Trajectories in Autoregressive Models. - Tian Yu Liu; Matthew Trager; Alessandro Achille; Pramuditha Perera; Luca Zancato; Stefano Soatto (ICLR, 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 002; Benjamin Bowman; Matthew Trager; Alessandro Achille; Stefano Soatto (NeurIPS, 2024)

NeRF-Insert: 3D Local Editing with Multimodal Control Signals. - Benet Oriol Sabat; Alessandro Achille; Matthew Trager; Stefano Soatto (CoRR, 2024)

Principles of Designing Robust Remote Face Anti-Spoofing Systems. - Xiang Xu; Tianchen Zhao; Zheng Zhang; Zhihua Li; Jon Wu; Alessandro Achille; Mani Srivastava 002 (CoRR, 2024)

Compositional Structures in Neural Embedding and Interaction Decompositions. - Matthew Trager; Alessandro Achille; Pramuditha Perera; Luca Zancato; Stefano Soatto (CoRR, 2024)

Long-context Protein Language Model. - Yingheng Wang; Zichen Wang 002; Gil Sadeh; Luca Zancato; Alessandro Achille; George Karypis; Huzefa Rangwala (CoRR, 2024)

Spacetime-Efficient Low-Depth Quantum State Preparation with Applications. - Kaiwen Gui; Alexander M. Dalzell; Alessandro Achille; Martin Suchara; Frederic T. Chong (Quantum, 2024)

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

LC-PLM: Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers. - Yingheng Wang; Zichen Wang 002; Gil Sadeh; Luca Zancato; Alessandro Achille; George Karypis; Huzefa Rangwala (Trans. Mach. Learn. Res., 2025)

Descriminative-Generative Custom Tokens for Vision-Language Models. - Pramuditha Perera; Matthew Trager; Luca Zancato; Alessandro Achille; Stefano Soatto (CoRR, 2025)