heteroscedastic regression

Fisher8: Stabilizing Neural Heteroscedastic Regression via Output-Layer Fisher Geometry UAI 2026 Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression ICLR 2025 Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification RSS 2025 SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits AISTATS 2024 TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression ICML 2024 Uncertainty-Aware Mean Opinion Score Prediction Interspeech 2024 Effective Bayesian Heteroscedastic Regression with Deep Neural Networks NeurIPS 2023 Faithful Heteroscedastic Regression with Neural Networks AISTATS 2023 Fast Expectation Propagation for Heteroscedastic, Lasso-Penalized, and Quantile Regression JMLR 2023 Near Optimal Heteroscedastic Regression with Symbiotic Learning COLT 2023 Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks AAAI 2023 Disentangling Uncertainty in Machine Translation Evaluation EMNLP 2022 Non-parametric Models for Non-negative Functions NeurIPS 2020 Selective Dyna-Style Planning Under Limited Model Capacity ICML 2020 Uncertainty-Aware Lookahead Factor Models for Quantitative Investing ICML 2020 Conformalized Quantile Regression NeurIPS 2019 Deterministic Variational Inference for Robust Bayesian Neural Networks ICLR 2019 Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression AISTATS 2018 Nonparametric Sharpe Ratio Function Estimation in Heteroscedastic Regression Models via Convex Optimization AISTATS 2018 Active Heteroscedastic Regression ICML 2017 Heteroscedastic Sequences: Beyond Gaussianity ICML 2016 Sequential Inference for Deep Gaussian Process AISTATS 2016 Learning Heteroscedastic Models by Convex Programming under Group Sparsity ICML 2013 Variational Bayesian Optimization for Runtime Risk-Sensitive Control RSS 2012 Gaussian Process Training with Input Noise NeurIPS 2011