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bayesian inference

1907 papers

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BI

Co-occurring keywords

variational inference (2069) markov chain monte carlo (725) gaussian process (1200) probabilistic modeling (852) uncertainty quantification (1393) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (864) probabilistic model (476)

Papers

Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks CVPR 2020
Optimal visual search based on a model of target detectability in natural images NIPS 2020
Bayesian Online Prediction of Change Points UAI 2020
Posterior Re-calibration for Imbalanced Datasets NIPS 2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference EMNLP 2020
Detecting Independent Pronoun Bias with Partially-Synthetic Data Generation EMNLP 2020
Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice NIPS 2020
Adaptive Neural Speech Enhancement with a Denoising Variational Autoencoder INTERSPEECH 2020
Learning under Model Misspecification: Applications to Variational and Ensemble methods NIPS 2020
Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses ACL 2020
Exponential ergodicity of mirror-Langevin diffusions NIPS 2020
A Unified View of Label Shift Estimation NIPS 2020
The Stanford Acuity Test: A Precise Vision Test Using Bayesian Techniques and a Discovery in Human Visual Response AAAI 2020
HARK: Harshness-Aware Sentiment Analysis Framework for Product Review (Student Abstract) AAAI 2020
Variational Inference for Sparse Gaussian Process Modulated Hawkes Process AAAI 2020
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback AAAI 2020
Diversified Bayesian Nonnegative Matrix Factorization AAAI 2020
A Bayesian Approach for Estimating Causal Effects from Observational Data AAAI 2020
Differentiable Algorithm for Marginalising Changepoints AAAI 2020
Residual Neural Processes AAAI 2020
Bayesian Bits: Unifying Quantization and Pruning NIPS 2020
Log-Linear Reformulation of the Noisy Channel Model for Document-Level Neural Machine Translation EMNLP 2020
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference ICML 2020
Variational Bayesian Monte Carlo with Noisy Likelihoods NIPS 2020
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support ICML 2020