stochastic neural network

Causal-StoNet: Causal Inference for High-Dimensional Complex Data ICLR 2024 Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks AISTATS 2024 Representational Dissimilarity Metric Spaces for Stochastic Neural Networks ICLR 2023 Conditionally Gaussian PAC-Bayes AISTATS 2022 How Sampling Impacts the Robustness of Stochastic Neural Networks NeurIPS 2022 Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network NeurIPS 2022 ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning UAI 2022 Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning ICML 2022 Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks NeurIPS 2022 Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception NeurIPS 2021 Simple and Effective Stochastic Neural Networks AAAI 2021 Weight-covariance alignment for adversarially robust neural networks ICML 2021 Graph Stochastic Neural Networks for Semi-supervised Learning NeurIPS 2020 Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach AAAI 2020 Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks ICML 2020 Stochastic Neural Network with Kronecker Flow AISTATS 2020 Inherent Weight Normalization in Stochastic Neural Networks NeurIPS 2019 Variance Networks: When Expectation Does Not Meet Your Expectations ICLR 2019 A Bayesian Approach to Generative Adversarial Imitation Learning NeurIPS 2018 A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks NeurIPS 2017 Stochastic Recurrent Neural Network for Speech Recognition Interspeech 2017 Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016 Fast Sampling-Based Inference in Balanced Neuronal Networks NeurIPS 2014 Learning Stochastic Feedforward Neural Networks NeurIPS 2013