Valdenegro-Toro, Matias

15 publications

CVPRW 2025 Uncertainty Quantification for Gradient-Based Explanations in Neural Networks Mihir Mulye, Matias Valdenegro-Toro

ICMLW 2024 Forecasting Smog Clouds with Deep Learning: A Proof-of-Concept Valentijn Oldenburg, Juan Cardenas-Cartagena, Matias Valdenegro-Toro

ECCVW 2024 Sanity Checks for Explanation Uncertainty Matias Valdenegro-Toro, Mihir Mulye

CVPRW 2023 Difficulty Estimation with Action Scores for Computer Vision Tasks Octavio Arriaga, Sebastian Palacio, Matias Valdenegro-Toro

ICCVW 2023 Sub-Ensembles for Fast Uncertainty Estimation in Neural Networks Matias Valdenegro-Toro

ICMLW 2023 Terrain Classification Enhanced with Uncertainty for Space Exploration Robots from Proprioceptive Data Mariela De Lucas Alvarez, Jichen Guo, Raul Dominguez, Matias Valdenegro-Toro

CVPRW 2022 A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement Matias Valdenegro-Toro, Daniel Saromo Mori

NeurIPSW 2022 Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression Levente Foldesi, Matias Valdenegro-Toro

CVPRW 2022 Self-Supervised Learning for Sonar Image Classification Alan Preciado-Grijalva, Bilal Wehbe, Miguel Bande Firvida, Matias Valdenegro-Toro

NeurIPSW 2021 Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning Aaqib Parvez Mohammed, Matias Valdenegro-Toro

NeurIPSW 2021 Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings Matias Valdenegro-Toro

CVPRW 2021 I Find Your Lack of Uncertainty in Computer Vision Disturbing Matias Valdenegro-Toro

ICCVW 2021 The Marine Debris Dataset for Forward-Looking Sonar Semantic Segmentation Deepak Singh, Matias Valdenegro-Toro

NeurIPSW 2020 Are Gradient-Based Saliency Maps Useful in Deep Reinforcement Learning? Matthias Rosynski, Frank Kirchner, Matias Valdenegro-Toro

NeurIPSW 2020 Know Where to Drop Your Weights: Towards Faster Uncertainty Estimation Akshatha Kamath, Dwaraknath Gnaneshwar, Matias Valdenegro-Toro