Deep Learning

ML4AD Best Papers Award Ceremony
Best Papers (one Peception and one Behavior) Awards.
Mar 4, 2025 3:45 PM 2025 AAAI ML4AD Workshop
Aleksandr Petiushko Александр Петюшко
Slides
ML4AD Best Papers Award Ceremony
Intelligent Mapping Solutions
AI-based Mapping solutions for Middle Mile.
Mar 4, 2025 8:20 AM 2025 WACV COOOL Challenge and Workshop
Aleksandr Petiushko Александр Петюшко
Slides
Intelligent Mapping Solutions
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
Integration of Position-Dependent Cross-Entropy loss function, Markov Logic Network, and Multimodal RAG with Vision Language Model (VLM), for achieving SotA results on Autonomous Driving benchmarks.
Jiawei Zhang, Xuan Yang, Taiqi Wang, Yu Yao, Aleksandr Petiushko Александр Петюшко, Bo Li
PDF Cite DOI arXiv
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
DiffScene: Diffusion-Based Safety-Critical Scenario Generation for Autonomous Vehicles
A guided diffusion-based scenario generation for safety-critical and realistic scenarios.
Chejian Xu, Aleksandr Petiushko Александр Петюшко, Ding Zhao, Bo Li
Cite Project
DiffScene: Diffusion-Based Safety-Critical Scenario Generation for Autonomous Vehicles
CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Driving
A novel approach to bring two worlds - Imitation and Reinforcement Learning - together for Safe Planning.
Jonathan Booher, Khashayar Rohanimanesh, Junhong Xu, Aleksandr Petiushko Александр Петюшко
PDF Cite DOI arXiv
CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Driving
Multi-Constraint Safe RL with Objective Suppression for Safety-Critical Applications
A novel approach to tackle the multiple constraints challenge in Safe RL.
Zihan Zhou, Jonathan Booher, Wei Liu, Aleksandr Petiushko Александр Петюшко, Animesh Garg
PDF Cite arXiv SymposiumWeb
Multi-Constraint Safe RL with Objective Suppression for Safety-Critical Applications
Mutual modality learning for video action classification
Mutual Modality (RGB, Optical Flow, RGBDiff, etc) Learning for Video Recognition.
Stepan Komkov, Maksim Dzabraev, Aleksandr Petiushko Александр Петюшко
PDF Cite Code Source Document DOI arXiv
Mutual modality learning for video action classification
Many Heads but One Brain: Fusion Brain - a Competition and a Single Multimodal Multitask Architecture
Multi-task multi-modal challenge, baseline, and methodology.
Daria Bakshandaeva, Denis Dimitrov, Vladimir Arkhipkin, Alex Shonenkov, Mark Potanin, Denis Karachev, Andrey Kuznetsov, Anton Voronov, Vera Davydova, Elena Tutubalina, Aleksandr Petiushko Александр Петюшко
PDF Cite Code Dataset Source Document DOI arXiv
Many Heads but One Brain: Fusion Brain - a Competition and a Single Multimodal Multitask Architecture
Nonparametric Uncertainty Quantification for Single Deterministic Neural Network
Elegant way of measuring both aleatoric and epistemic uncertainties for neural nets.
Nikita Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin, Fedor Noskov, Alexander Fishkov, Artem Shelmanov, Artem Vazhentsev, Aleksandr Petiushko Александр Петюшко, Maxim Panov
PDF Cite Slides Source Document arXiv OpenReview Conf
Nonparametric Uncertainty Quantification for Single Deterministic Neural Network
Smoothed Embeddings for Certified Few-Shot Learning
Geometrical approach for certified few-shot learning via randomized smoothing of templates.
Mikhail Pautov, Olesya Kuznetsova, Nurislam Tursynbek, Aleksandr Petiushko Александр Петюшко, Ivan Oseledets
PDF Cite Poster Slides Source Document arXiv OpenReview Conf
Smoothed Embeddings for Certified Few-Shot Learning