Alessandro Achille

Orcid: 0000-0002-8163-8326

According to our database¹, Alessandro Achille authored at least 60 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of three.

Timeline

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In proceedings

Article

PhD thesis

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Links

On csauthors.net:

Bibliography

2024

Spacetime-Efficient Low-Depth Quantum State Preparation with Applications.

[BibT_eX]

[DOI]

Quantum, February, 2024

CPR: Retrieval Augmented Generation for Copyright Protection.

[BibT_eX]

[DOI]

CoRR, 2024

Multi-Modal Hallucination Control by Visual Information Grounding.

[BibT_eX]

[DOI]

CoRR, 2024

Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Meaning Representations from Trajectories in Autoregressive Models.

[BibT_eX]

[DOI]

CoRR, 2023

Critical Learning Periods Emerge Even in Deep Linear Networks.

[BibT_eX]

[DOI]

Michael Kleinman

Alessandro Achille

Stefano Soatto

CoRR, 2023

Training Data Protection with Compositional Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2023

Towards Visual Foundational Models of Physical Scenes.

[BibT_eX]

[DOI]

CoRR, 2023

Prompt Algebra for Task Composition.

[BibT_eX]

[DOI]

CoRR, 2023

AI Model Disgorgement: Methods and Choices.

[BibT_eX]

[DOI]

CoRR, 2023

Introspective Cross-Attention Probing for Lightweight Transfer of Pre-trained Models.

[BibT_eX]

[DOI]

CoRR, 2023

Linear Spaces of Meanings: the Compositional Language of VLMs.

[BibT_eX]

[DOI]

CoRR, 2023

Gacs-Korner Common Information Variational Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Leveraging sparse and shared feature activations for disentangled representation learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Your representations are in the network: composable and parallel adaptation for large scale models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Linear Spaces of Meanings: Compositional Structures in Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

SAFE: Machine Unlearning With Shard Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Train/Test-Time Adaptation with Retrieval.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Critical Learning Periods for Multisensory Integration in Deep Networks.

[BibT_eX]

[DOI]

Michael Kleinman

Alessandro Achille

Stefano Soatto

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

A Meta-Learning Approach to Predicting Performance and Data Requirements.

[BibT_eX]

[DOI]

Achin Jain

Gurumurthy Swaminathan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Integral Continual Learning Along the Tangent Vector Field of Tasks.

[BibT_eX]

[DOI]

CoRR, 2022

On Binding Objects to Symbols: Learning Physical Concepts to Understand Real from Fake.

[BibT_eX]

[DOI]

Alessandro Achille

Stefano Soatto

CoRR, 2022

Towards Differential Relational Privacy and its use in Question Answering.

[BibT_eX]

[DOI]

CoRR, 2022

Stacked Residuals of Dynamic Layers for Time Series Anomaly Detection.

[BibT_eX]

[DOI]

CoRR, 2022

On Leave-One-Out Conditional Mutual Information For Generalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DIVA: Dataset Derivative of a Learning Task.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Task Adaptive Parameter Sharing for Multi-Task Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Mixed Differential Privacy in Computer Vision.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Redundant Information Neural Estimation.

[BibT_eX]

[DOI]

Entropy, 2021

A linearized framework and a new benchmark for model selection for fine-tuning.

[BibT_eX]

[DOI]

CoRR, 2021

On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Structured Prediction as Translation between Augmented Natural Languages.

[BibT_eX]

[DOI]

Cícero Nogueira dos Santos

Bing Xiang

Stefano Soatto

Proceedings of the 9th International Conference on Learning Representations, 2021

Usable Information and Evolution of Optimal Representations During Training.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Estimating informativeness of samples with Smooth Unique Information.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

LayoutTransformer: Layout Generation and Completion with Self-attention.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Mixed-Privacy Forgetting in Deep Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

LQF: Linear Quadratic Fine-Tuning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Adversarial Training Reduces Information and Improves Transferability.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Layout Generation and Completion with Self-attention.

[BibT_eX]

[DOI]

CoRR, 2020

Predicting Training Time Without Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Incremental Few-Shot Meta-learning via Indirect Discriminant Alignment.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations.

[BibT_eX]

[DOI]

Aditya Golatkar

Alessandro Achille

Stefano Soatto

Proceedings of the Computer Vision - ECCV 2020, 2020

Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks.

[BibT_eX]

[DOI]

Aditya Golatkar

Alessandro Achille

Stefano Soatto

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Emergent Properties of Deep Neural Networks.

[BibT_eX]

[DOI]

Alessandro Achille

PhD thesis, 2019

TextTubes for Detecting Curved Text in the Wild.

[BibT_eX]

[DOI]

Joël Seytre

Jon Wu

Alessandro Achille

CoRR, 2019

Toward Understanding Catastrophic Forgetting in Continual Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Where is the Information in a Deep Neural Network?

[BibT_eX]

[DOI]

Alessandro Achille

Stefano Soatto

CoRR, 2019

The Information Complexity of Learning Tasks, their Structure and their Distance.

[BibT_eX]

[DOI]

CoRR, 2019

Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence.

[BibT_eX]

[DOI]

Aditya Golatkar

Alessandro Achille

Stefano Soatto

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Critical Learning Periods in Deep Networks.

[BibT_eX]

[DOI]

Alessandro Achille

Matteo Rovere

Stefano Soatto

Proceedings of the 7th International Conference on Learning Representations, 2019

Task2Vec: Task Embedding for Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Information Dropout: Learning Optimal Representations Through Noisy Computation.

[BibT_eX]

[DOI]

Alessandro Achille

Stefano Soatto

IEEE Trans. Pattern Anal. Mach. Intell., 2018

Emergence of Invariance and Disentanglement in Deep Representations.

[BibT_eX]

[DOI]

Alessandro Achille

Stefano Soatto

J. Mach. Learn. Res., 2018

The Dynamics of Differential Learning I: Information-Dynamics and Task Reachability.

[BibT_eX]

[DOI]

Alessandro Achille

Glen Mbeng

Stefano Soatto

CoRR, 2018

A Separation Principle for Control in the Age of Deep Learning.

[BibT_eX]

[DOI]

Alessandro Achille

Stefano Soatto

Annu. Rev. Control. Robotics Auton. Syst., 2018

Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies.

[BibT_eX]

[DOI]

Alessandro Achille

Tom Eccles

Loïc Matthey

Christopher P. Burgess

Nicholas Watters

Alexander Lerchner

Irina Higgins

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Critical Learning Periods in Deep Neural Networks.

[BibT_eX]

[DOI]

Alessandro Achille

Matteo Rovere

Stefano Soatto

CoRR, 2017

On the Emergence of Invariance and Disentangling in Deep Representations.

[BibT_eX]

[DOI]

Alessandro Achille

Stefano Soatto

CoRR, 2017

2016

Information Dropout: learning optimal representations through noise.

[BibT_eX]

[DOI]

Alessandro Achille

Stefano Soatto

CoRR, 2016

Alessandro Achille

Timeline

Legend:

Links

On csauthors.net:

Bibliography

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