An elementary introduction to information geometry

17 August 2018

Papers citing "An elementary introduction to information geometry"

25 / 25 papers shown

Title
Variational Formulation of the Particle Flow Particle Filter Yinzhuang Yi Jorge Cortés Nikolay Atanasov 36 0 0 06 May 2025
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges Ce Ju Reinmar J. Kobler Antoine Collas M. Kawanabe Cuntai Guan Bertrand Thirion 43 0 0 26 Apr 2025
Learning to Assist Humans without Inferring Rewards Vivek Myers Evan Ellis Sergey Levine Benjamin Eysenbach Anca Dragan 43 2 0 17 Jan 2025
Wasserstein Flow Matching: Generative modeling over families of distributions Doron Haviv Aram-Alexandre Pooladian D. Pe’er Brandon Amos OOD 37 0 0 01 Nov 2024
Cartan moving frames and the data manifolds Eliot Tron Rita Fioresi Nicolas Couellan Stéphane Puechmorel 51 1 0 18 Sep 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 68 1 0 27 May 2024
The Fisher-Rao geometry of CES distributions Florent Bouchard A. Breloy Antoine Collas Alexandre Renaux G. Ginolhac 18 5 0 02 Oct 2023
Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning V. Usatyuk Sergey Egorov Denis Sapozhnikov 29 3 0 28 Jul 2023
Neural FIM for learning Fisher Information Metrics from point cloud data O. Fasina Guilluame Huguet Alexander Tong Yanlei Zhang Guy Wolf Maximilian Nickel Ian M. Adelstein Smita Krishnaswamy 30 3 0 01 Jun 2023
Bayesian Renormalization D. Berman Marc S. Klinger A. G. Stapleton 32 16 0 17 May 2023
Playing it safe: information constrains collective betting strategies P. Fleig V. Balasubramanian 18 0 0 18 Apr 2023
Codivergences and information matrices A. Derumigny Johannes Schmidt-Hieber 19 1 0 14 Mar 2023
Properties of the Concrete distribution D. D. Chow 24 0 0 02 Nov 2022
Loss Minimization through the Lens of Outcome Indistinguishability Parikshit Gopalan Lunjia Hu Michael P. Kim Omer Reingold Udi Wieder UQCV 35 31 0 16 Oct 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents Alessandro Barp Lancelot Da Costa G. Francca Karl J. Friston Mark Girolami Michael I. Jordan G. Pavliotis 31 25 0 20 Mar 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 52 20 0 31 Jan 2022
Merging Models with Fisher-Weighted Averaging Michael Matena Colin Raffel FedML MoMe 50 352 0 18 Nov 2021
On the Importance of Firth Bias Reduction in Few-Shot Classification Saba Ghaffari Ehsan Saleh David A. Forsyth Yu-xiong Wang 32 13 0 06 Oct 2021
Fast approximations of the Jeffreys divergence between univariate Gaussian mixture models via exponential polynomial densities Frank Nielsen 35 12 0 13 Jul 2021
Pulling back information geometry Georgios Arvanitidis Miguel González Duque Alison Pouplin Dimitris Kalatzis Søren Hauberg DRL 9 14 0 09 Jun 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 22 17 0 06 May 2021
Cumulant-free closed-form formulas for some common (dis)similarities between densities of an exponential family Frank Nielsen Richard Nock 13 3 0 05 Mar 2020
A New Lower Bound for Kullback-Leibler Divergence Based on Hammersley-Chapman-Robbins Bound T. Nishiyama 14 9 0 29 Jun 2019
A Riemanian Approach to Blob Detection in Manifold-Valued Images Aleksei Shestov Mikhail Kumskov 49 24 0 31 May 2019
Statistical exponential families: A digest with flash cards Frank Nielsen Vincent Garcia 88 183 0 25 Nov 2009