Papers
1,821 papers found
A variational approximation for analyzing the dynamics of panel data
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant et al.
Learnable uncertainty under Laplace approximations
Agustinus Kristiadi, Matthias Hein, Philipp Hennig
Approximation algorithm for submodular maximization under submodular cover
Naoto Ohsaka, Tatsuya Matsuoka
Combining pseudo-point and state space approximations for sum-separable Gaussian Processes
Will Tebbutt, Arno Solin, Richard E. Turner
NeuroBE: Escalating neural network approximations of Bucket Elimination
Sakshi Agarwal, Kalev Kask, Alex Ihler et al.
Active approximately metric-fair learning
Yiting Cao, Chao Lan
Fixing the Bethe approximation: How structural modifications in a graph improve belief propagation
Harald Leisenberger, Franz Pernkopf, Christian Knoll
Laplace approximated Gaussian process state-space models
Jakob Lindinger, Barbara Rakitsch, Christoph Lippert
Approximating probabilistic explanations via supermodular minimization
Louenas Bounia, Frederic Koriche
Finite-sample guarantees for Nash Q-learning with linear function approximation
Pedro Cisneros-Velarde, Sanmi Koyejo
The Shrinkage-Delinkage Trade-off: an Analysis of Factorized Gaussian Approximations for Variational Inference
Charles C. Margossian, Lawrence K. Saul
KrADagrad: Kronecker approximation-domination gradient preconditioned stochastic optimization
Jonathan Mei, Alexander Moreno, Luke Walters
Jana: Jointly amortized neural approximation of complex Bayesian models
Stefan T. Radev, Marvin Schmitt, Valentin Pratz et al.
Approximately Bayes-optimal pseudo-label selection
Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti et al.
RNNP: A Robust Few-Shot Learning Approach
Pratik Mazumder, Pravendra Singh, Vinay P. Namboodiri
Meta Approach to Data Augmentation Optimization
Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe et al.
An Experimental Comparison of Multi-View Stereo Approaches on Satellite Images
Alvaro Gómez, Gregory Randall, Gabriele Facciolo et al.
SVD-NAS: Coupling Low-Rank Approximation and Neural Architecture Search
Zhewen Yu, Christos-Savvas Bouganis
Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo
Maximilian Weiherer, Finn Klein, Bernhard Egger
Precise Integral in NeRFs: Overcoming the Approximation Errors of Numerical Quadrature
Boyuan Zhang, Zhenliang He, Meina Kan et al.
Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection
Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov
On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approaches
Florian Hofherr, Bjoern Haefner, Daniel Cremers
GEXIA: Granularity Expansion and Iterative Approximation for Scalable Multi-Grained Video-Language Learning
Yicheng Wang, Zhikang Zhang, Jue Wang et al.