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05/23/2023
SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models
A potent class of generative models known as Diffusion Probabilistic Mod...
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06/21/2022
Riemannian data-dependent randomized smoothing for neural networks certification
Certification of neural networks is an important and challenging problem...
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06/16/2022
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening
We investigate the problems and challenges of evaluating the robustness ...
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05/24/2022
Realization Theory Of Recurrent Neural ODEs Using Polynomial System Embeddings
In this paper we show that neural ODE analogs of recurrent (ODE-RNN) and...
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04/07/2021
Improving Robustness of Deep Reinforcement Learning Agents: Environment Attacks based on Critic Networks
To improve policy robustness of deep reinforcement learning agents, a li...
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11/24/2020
Stochastic sparse adversarial attacks
Adversarial attacks of neural network classifiers (NNC) and the use of r...
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07/12/2020
Probabilistic Jacobian-based Saliency Maps Attacks
Machine learning models have achieved spectacular performances in variou...
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02/05/2020
FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains
In the realm of autonomous transportation, there have been many initiati...
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07/02/2019
Learning graph-structured data using Poincaré embeddings and Riemannian K-means algorithms
Recent literature has shown several benefits of hyperbolic embedding of ...
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07/30/2018
Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with evaluation on a ground truth
- Both Lidars and Radars are sensors for obstacle detection. While Lidar...
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07/16/2018
