Eugene Belilovsky

According to our database, Eugene Belilovsky authored at least 71 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Simple and Scalable Strategies to Continually Pre-train Large Language Models.

Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish

Trans. Mach. Learn. Res., 2024

Non-Uniform Parameter-Wise Model Merging.

Albert Manuel Orozco Camacho, Stefan Horoi, Guy Wolf, Eugene Belilovsky

CoRR, 2024

Towards motion from video diffusion models.

Paul Janson, Tiberiu Popa, Eugene Belilovsky

CoRR, 2024

Not Only the Last-Layer Features for Spurious Correlations: All Layer Deep Feature Reweighting.

Humza Wajid Hameed, Géraldin Nanfack, Eugene Belilovsky

CoRR, 2024

Accelerating Training with Neuron Interaction and Nowcasting Networks.

Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien

CoRR, 2024

Controlling Forgetting with Test-Time Data in Continual Learning.

Vaibhav Singh, Rahaf Aljundi, Eugene Belilovsky

CoRR, 2024

ACCO: Accumulate while you Communicate, Hiding Communications in Distributed LLM Training.

Adel Nabli, Louis Fournier, Pierre Erbacher, Louis Serrano, Eugene Belilovsky, Edouard Oyallon

CoRR, 2024

PETRA: Parallel End-to-end Training with Reversible Architectures.

Stéphane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

CoRR, 2024

From Feature Visualization to Visual Circuits: Effect of Adversarial Model Manipulation.

Géraldin Nanfack, Michael Eickenberg, Eugene Belilovsky

CoRR, 2024

Temporally Consistent Object Editing in Videos using Extended Attention.

AmirHossein Zamani, Amir G. Aghdam, Tiberiu Popa, Eugene Belilovsky

CoRR, 2024

μLO: Compute-Efficient Meta-Generalization of Learned Optimizers.

Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky

CoRR, 2024

WASH: Train your Ensemble with Communication-Efficient Weight Shuffling, then Average.

Louis Fournier, Adel Nabli, Masih Aminbeidokhti, Marco Pedersoli, Eugene Belilovsky, Edouard Oyallon

CoRR, 2024

AdaFisher: Adaptive Second Order Optimization via Fisher Information.

Damien Martins Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini

CoRR, 2024

Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation.

Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod, An Tang, Guy Cloutier, Guy Wolf, Michael Eickenberg, Eugene Belilovsky

CoRR, 2024

Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis.

Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky, Guy Wolf

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Model Breadcrumbs: Scaling Multi-task Model Merging with Sparse Masks.

MohammadReza Davari, Eugene Belilovsky

Proceedings of the Computer Vision - ECCV 2024, 2024

Adversarial Attacks on the Interpretation of Neuron Activation Maximization.

Géraldin Nanfack, Alexander Fulleringer, Jonathan Marty, Michael Eickenberg, Eugene Belilovsky

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Gradient Masked Averaging for Federated Learning.

Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Irina Rish, Eugene Belilovsky

Trans. Mach. Learn. Res., 2023

Can We Learn Communication-Efficient Optimizers?

Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky

CoRR, 2023

DragD3D: Vertex-based Editing for Realistic Mesh Deformations using 2D Diffusion Priors.

Tianhao Xie, Eugene Belilovsky, Sudhir Mudur, Tiberiu Popa

CoRR, 2023

Continual Pre-Training of Large Language Models: How to (re)warm your model?

Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort

CoRR, 2023

Imitation from Observation With Bootstrapped Contrastive Learning.

Medric Sonwa, Johanna Hansen, Eugene Belilovsky

CoRR, 2023

Local Learning with Neuron Groups.

Adeetya Patel, Michael Eickenberg, Eugene Belilovsky

CoRR, 2023

A²CiD²: Accelerating Asynchronous Communication in Decentralized Deep Learning.

Adel Nabli, Eugene Belilovsky, Edouard Oyallon

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

Guiding The Last Layer in Federated Learning with Pre-Trained Models.

Gwen Legate, Nicolas Bernier, Lucas Page-Caccia, Edouard Oyallon, Eugene Belilovsky

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

Can Forward Gradient Match Backpropagation?

Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

Proceedings of the International Conference on Machine Learning, 2023

Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning.

Nader Asadi, MohammadReza Davari, Sudhir Mudur, Rahaf Aljundi, Eugene Belilovsky

Proceedings of the International Conference on Machine Learning, 2023

Reliability of CKA as a Similarity Measure in Deep Learning.

MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Simulated Annealing in Early Layers Leads to Better Generalization.

AmirMohammad Sarfi, Zahra Karimpour, Muawiz Chaudhary, Nasir Mohammad Khalid, Mirco Ravanelli, Sudhir Mudur, Eugene Belilovsky

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

Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning.

Gwen Legate, Lucas Caccia, Eugene Belilovsky

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Text to Mesh Without 3D Supervision Using Limit Subdivision.

Nasir Mohammad Khalid, Tianhao Xie, Eugene Belilovsky, Tiberiu Popa

CoRR, 2022

Tackling Online One-Class Incremental Learning by Removing Negative Contrasts.

Nader Asadi, Sudhir Mudur, Eugene Belilovsky

CoRR, 2022

CLIP-Mesh: Generating textured meshes from text using pretrained image-text models.

Nasir Mohammad Khalid, Tianhao Xie, Eugene Belilovsky, Tiberiu Popa

Proceedings of the SIGGRAPH Asia 2022 Conference Papers, 2022

Towards Scaling Difference Target Propagation by Learning Backprop Targets.

Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio

Proceedings of the International Conference on Machine Learning, 2022

New Insights on Reducing Abrupt Representation Change in Online Continual Learning.

Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky

Proceedings of the Tenth International Conference on Learning Representations, 2022

Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning.

Moslem Yazdanpanah, Aamer Abdul Rahman, Muawiz Chaudhary, Christian Desrosiers, Mohammad Havaei, Eugene Belilovsky, Samira Ebrahimi Kahou

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

Parametric Scattering Networks.

Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf

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

Probing Representation Forgetting in Supervised and Unsupervised Continual Learning.

MohammadReza Davari, Nader Asadi, Sudhir Mudur, Rahaf Aljundi, Eugene Belilovsky

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

2021

Parametric Scattering Networks.

Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf

CoRR, 2021

Learning Compositional Shape Priors for Few-Shot 3D Reconstruction.

Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky

CoRR, 2021

Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning.

Eugene Belilovsky, Louis Leconte, Lucas Caccia, Michael Eickenberg, Edouard Oyallon

CoRR, 2021

Reducing Representation Drift in Online Continual Learning.

Lucas Caccia, Rahaf Aljundi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky

CoRR, 2021

The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods.

Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon

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

Generative Compositional Augmentations for Scene Graph Prediction.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

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

2020

Kymatio: Scattering Transforms in Python.

Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg

J. Mach. Learn. Res., 2020

Generative Graph Perturbations for Scene Graph Prediction.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

CoRR, 2020

Online Learned Continual Compression with Adaptive Quantization Modules.

Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau

Proceedings of the 37th International Conference on Machine Learning, 2020

Decoupled Greedy Learning of CNNs.

Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

Proceedings of the 37th International Conference on Machine Learning, 2020

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors.

Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky

Proceedings of the Computer Vision - ECCV 2020, 2020

A Simple and Scalable Shape Representation for 3D Reconstruction.

Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders P. Eriksson

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation.

Boris Knyazev, Harm de Vries, Catalina Cangea, Graham W. Taylor, Aaron C. Courville, Eugene Belilovsky

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

Scattering Networks for Hybrid Representation Learning.

Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Online Learned Continual Compression with Stacked Quantization Module.

Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau

CoRR, 2019

Online Continual Learning with Maximally Interfered Retrieval.

Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Min Lin, Laurent Charlin, Tinne Tuytelaars

CoRR, 2019

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering.

Catalina Cangea, Eugene Belilovsky, Pietro Liò, Aaron C. Courville

Proceedings of the Visually Grounded Interaction and Language (ViGIL), 2019

Online Continual Learning with Maximal Interfered Retrieval.

Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, Lucas Page-Caccia

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

Greedy Layerwise Learning Can Scale To ImageNet.

Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

Proceedings of the 36th International Conference on Machine Learning, 2019

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering.

Catalina Cangea, Eugene Belilovsky, Aaron C. Courville

Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018

Structured Sparse Learning on Graphs in High-Dimensional Data with Applications to NeuroImaging. (Apprentissage de graphes structuré et parcimonieux dans des données de haute dimension avec applications à l'imagerie cérébrale).

Eugene Belilovsky

PhD thesis, 2018

Kymatio: Scattering Transforms in Python.

Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg

CoRR, 2018

Blindfold Baselines for Embodied QA.

Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville

CoRR, 2018

Compressing the Input for CNNs with the First-Order Scattering Transform.

Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

Learning to Discover Sparse Graphical Models.

Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko

Proceedings of the 34th International Conference on Machine Learning, 2017

Joint Embeddings of Scene Graphs and Images.

Eugene Belilovsky, Matthew B. Blaschko, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel

Proceedings of the 5th International Conference on Learning Representations, 2017

Scaling the Scattering Transform: Deep Hybrid Networks.

Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko

Proceedings of the IEEE International Conference on Computer Vision, 2017

2016

Fast Non-Parametric Tests of Relative Dependency and Similarity.

Wacha Bounliphone, Eugene Belilovsky, Arthur Tenenhaus, Ioannis Antonoglou, Arthur Gretton, Matthew B. Blaschko

CoRR, 2016

A Test of Relative Similarity For Model Selection in Generative Models.

Wacha Bounliphone, Eugene Belilovsky, Matthew B. Blaschko, Ioannis Antonoglou, Arthur Gretton

Proceedings of the 4th International Conference on Learning Representations, 2016

Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity.

Eugene Belilovsky, Gaël Varoquaux, Matthew B. Blaschko

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Convex relaxations of penalties for sparse correlated variables with bounded total variation.

Eugene Belilovsky, Andreas Argyriou, Gaël Varoquaux, Matthew B. Blaschko

Mach. Learn., 2015

Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm.

Eugene Belilovsky, Katerina Gkirtzou, Michail Misyrlis, Anna B. Konova, Jean Honorio, Nelly Alia-Klein, Rita Z. Goldstein, Dimitris Samaras, Matthew B. Blaschko

Comput. Medical Imaging Graph., 2015

2009

Generalized cyclic transformations in speaker-independent speech recognition.

Florian Müller, Eugene Belilovsky, Alfred Mertins

Proceedings of the 2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009