Eugene Belilovsky
32 papers · 2016–2026 · 9 venues · across top CS/AI venues
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Research topics
Machine Learning
(25)
Deep Learning
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Optimization & Theory
(15)
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(9)
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Learning Types Β· Machine Learning
(7)
Artificial Intelligence
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neural network
(4)
representation learning
(4)
convolutional neural network
(3)
continual learning
(3)
catastrophic forgetting
(3)
unsupervised learning
(2)
contrastive learning
(2)
wavelet scattering transform
(2)
few-shot learning
(2)
neural network training
(2)
transfer learning
(2)
domain adaptation
(2)
image classification
(2)
experience replay
(2)
neural network optimization
(2)
distributed training
(2)
greedy learning
(2)
layer-wise training
(2)
batch normalization
(2)
object recognition
(1)
Papers
End-to-End Fine-Tuning of 3D Texture Generation using Differentiable Rewards
WACV 2026
Sketch-guided Cage-based 3D Gaussian Splatting Deformation
WACV 2026
Test Time Adaptation Using Adaptive Quantile Recalibration
WACV 2026
Accelerating Training with Neuron Interaction and Nowcasting Networks
ICLR 2025
AdaFisher: Adaptive Second Order Optimization via Fisher Information
ICLR 2025
PETRA: Parallel End-to-end Training with Reversible Architectures
ICLR 2025
Adversarial Attacks on the Interpretation of Neuron Activation Maximization
AAAI 2024
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis
ICML 2024
Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Masks
ECCV 2024
A^2CiD^2: Accelerating Asynchronous Communication in Decentralized Deep Learning
NeurIPS 2023
Can Forward Gradient Match Backpropagation?
ICML 2023
Guiding The Last Layer in Federated Learning with Pre-Trained Models
NeurIPS 2023
Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning
ICML 2023
Reliability of CKA as a Similarity Measure in Deep Learning
ICLR 2023
Simulated Annealing in Early Layers Leads to Better Generalization
CVPR 2023
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
ICLR 2022
Parametric Scattering Networks
CVPR 2022
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning
CVPR 2022
Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning
CVPR 2022
Towards Scaling Difference Target Propagation by Learning Backprop Targets
ICML 2022
Generative Compositional Augmentations for Scene Graph Prediction
ICCV 2021
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
ICLR 2021
Decoupled Greedy Learning of CNNs
ICML 2020
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
ECCV 2020
Kymatio: Scattering Transforms in Python
JMLR 2020
Online Learned Continual Compression with Adaptive Quantization Modules
ICML 2020
Greedy Layerwise Learning Can Scale To ImageNet
ICML 2019
Online Continual Learning with Maximal Interfered Retrieval
NeurIPS 2019
Compressing the Input for CNNs with the First-Order Scattering Transform
ECCV 2018
Learning to Discover Sparse Graphical Models
ICML 2017
Scaling the Scattering Transform: Deep Hybrid Networks
ICCV 2017
Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity
NeurIPS 2016