Papers
938 papers found
No-regret approximate inference via Bayesian optimisation
Rafael Oliveira, Lionel Ott, Fabio Ramos
No-regret learning with high-probability in adversarial Markov decision processes
Mahsa Ghasemi, Abolfazl Hashemi, Haris Vikalo et al.
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation
Xiaohui Zeng, Raquel Urtasun, Richard Zemel et al.
On random kernels of residual architectures
Etai Littwin, Tomer Galanti, Lior Wolf
On the distributional properties of adaptive gradients
Zhiyi Zhang, Ziyin Liu
On the distribution of penultimate activations of classification networks
Minkyo Seo, Yoonho Lee, Suha Kwak
On the effects of quantisation on model uncertainty in Bayesian neural networks
Martin Ferianc, Partha Maji, Matthew Mattina et al.
Optimized auxiliary particle filters: adapting mixture proposals via convex optimization
Nicola Branchini, Víctor Elvira
PALM: Probabilistic area loss Minimization for Protein Sequence Alignment
Fan Ding, Nan Jiang, Jianzhu Ma et al.
Partial Identifiability in Discrete Data with Measurement Error
Noam Finkelstein, Roy Adams, Suchi Saria et al.
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks
Xufang Luo, Qi Meng, Wei Chen et al.
Path dependent structural equation models
Ranjani Srinivasan, Jaron J. R. Lee, Rohit Bhattacharya et al.
PLSO: A generative framework for decomposing nonstationary time-series into piecewise stationary oscillatory components
Andrew H. Song, Demba Ba, Emery N. Brown
Possibilistic preference elicitation by minimax regret
Loïc Adam, Sebastien Destercke
Post-hoc loss-calibration for Bayesian neural networks
Meet P. Vadera, Soumya Ghosh, Kenney Ng et al.
Principal component analysis in the stochastic differential privacy model
Fanhua Shang, Zhihui Zhang, Tao Xu et al.
Probabilistic DAG search
Julia Grosse, Cheng Zhang, Philipp Hennig
Probabilistic selection of inducing points in sparse Gaussian processes
Anders Kirk Uhrenholt, Valentin Charvet, Bjørn Sand Jensen
Probabilistic task modelling for meta-learning
Cuong C. Nguyen, Thanh-Toan Do, Gustavo Carneiro
Proceedings of the thirty-seventh conference on Uncertainty in Artificial Intelligence — Preface
Cassio de Campos, Marloes H. Maathuis, Erik Quaeghebeur
PROVIDE: a probabilistic framework for unsupervised video decomposition
Polina Zablotskaia, Edoardo A. Dominici, Leonid Sigal et al.
pRSL: Interpretable multi-label stacking by learning probabilistic rules
Michael Kirchhof, Lena Schmid, Christopher Reining et al.
q-Paths: Generalizing the geometric annealing path using power means
Vaden Masrani, Rob Brekelmans, Thang Bui et al.
Random probabilistic circuits
Nicola Di Mauro, Gennaro Gala, Marco Iannotta et al.
Regstar: efficient strategy synthesis for adversarial patrolling games
David Klaška, Antonín Kučera, Vít Musil et al.