Evgeny Burnaev

Motivating Next-Gen Accelerators with Flexible N:M Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches ACL 2026 AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents IJCAI 2025 GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs ACL 2025 Feature-Level Insights into Artificial Text Detection with Sparse Autoencoders ACL 2025 A3D: Does Diffusion Dream about 3D Alignment? ICLR 2025 RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning Tasks AISTATS 2025 Inverse Bridge Matching Distillation ICML 2025 Quantifying Logical Consistency in Transformers via Query-Key Alignment EMNLP 2025 Factored-NeuS: Reconstructing Surfaces, Illumination, and Materials of Possibly Glossy Objects CVPR 2025 Rethinking Optimal Transport in Offline Reinforcement Learning NIPS 2024 Light Schrödinger Bridge ICLR 2024 Neural Optimal Transport with General Cost Functionals ICLR 2024 Energy-guided Entropic Neural Optimal Transport ICLR 2024 Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation ICML 2024 Estimating Barycenters of Distributions with Neural Optimal Transport ICML 2024 Scalar Function Topology Divergence: Comparing Topology of 3D Objects ECCV 2024 Light and Optimal Schrödinger Bridge Matching ICML 2024 Disentanglement Learning via Topology ICML 2024 Adversarial Schrödinger Bridge Matching NIPS 2024 Light Unbalanced Optimal Transport NIPS 2024 Energy-Guided Continuous Entropic Barycenter Estimation for General Costs NIPS 2024 Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark NIPS 2023 Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts NIPS 2023 Extremal Domain Translation with Neural Optimal Transport NIPS 2023 Entropic Neural Optimal Transport via Diffusion Processes NIPS 2023 Sphere-Guided Training of Neural Implicit Surfaces CVPR 2023 Multi-Sensor Large-Scale Dataset for Multi-View 3D Reconstruction CVPR 2023 Learning topology-preserving data representations ICLR 2023 Kernel Neural Optimal Transport ICLR 2023 Neural Optimal Transport ICLR 2023 Topological Data Analysis for Speech Processing INTERSPEECH 2023 NPBG++: Accelerating Neural Point-Based Graphics CVPR 2022 Generative Modeling with Optimal Transport Maps ICLR 2022 Representation Topology Divergence: A Method for Comparing Neural Network Representations. ICML 2022 Wasserstein Iterative Networks for Barycenter Estimation NIPS 2022 Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport? NIPS 2022 Acceptability Judgements via Examining the Topology of Attention Maps EMNLP 2022 Manifold Topology Divergence: a Framework for Comparing Data Manifolds. NIPS 2021 Making DensePose Fast and Light WACV 2021 Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark NIPS 2021 Towards Part-Based Understanding of RGB-D Scans CVPR 2021 Artificial Text Detection via Examining the Topology of Attention Maps EMNLP 2021 BooVAE: Boosting Approach for Continual Learning of VAE NIPS 2021 Wasserstein-2 Generative Networks ICLR 2021 Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization ICLR 2021 Large-Scale Wasserstein Gradient Flows NIPS 2021 CAD-Deform: Deformable Fitting of CAD Models to 3D Scans ECCV 2020 Deep Vectorization of Technical Drawings ECCV 2020 Bayesian Sparsification of Deep C-valued Networks ICML 2020 Latent Convolutional Models ICLR 2019 ABC: A Big CAD Model Dataset for Geometric Deep Learning CVPR 2019 Perceptual Deep Depth Super-Resolution ICCV 2019 Anonymous Walk Embeddings ICML 2018 Quadrature-based features for kernel approximation NIPS 2018 Minimax Approach to Variable Fidelity Data Interpolation AISTATS 2017 Efficiency of conformalized ridge regression COLT 2014