conftrace_

Artificial Intelligence

72,274 papers (0 classified directly here)

Subtopics

Core AI (59,089) Learning Paradigms (14,108) Bayesian & Probabilistic (4,335)

Papers per year

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22
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14833
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Papers (including subtopics)

On Relating Explanations and Adversarial Examples NIPS 2019
Single-Model Uncertainties for Deep Learning NIPS 2019
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric NIPS 2019
Adversarial training for free! NIPS 2019
Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks NIPS 2019
Addressing Failure Prediction by Learning Model Confidence NIPS 2019
Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes NIPS 2019
Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness NIPS 2019
Towards Automatic Concept-based Explanations NIPS 2019
Defending Neural Backdoors via Generative Distribution Modeling NIPS 2019
Offline Contextual Bayesian Optimization NIPS 2019
Uncertainty on Asynchronous Time Event Prediction NIPS 2019
Hierarchical Decision Making by Generating and Following Natural Language Instructions NIPS 2019
Sobolev Independence Criterion NIPS 2019
Reconciling meta-learning and continual learning with online mixtures of tasks NIPS 2019
Sparse Variational Inference: Bayesian Coresets from Scratch NIPS 2019
Policy Evaluation with Latent Confounders via Optimal Balance NIPS 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond NIPS 2019
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI NIPS 2019
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness NIPS 2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation NIPS 2019
Maximum Entropy Monte-Carlo Planning NIPS 2019
Full-Gradient Representation for Neural Network Visualization NIPS 2019
Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback NIPS 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle NIPS 2019