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An elementary introduction to information geometry

17 August 2018

Papers citing "An elementary introduction to information geometry"

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Title
Foundations of Top- $k$ Decoding For Language Models Georgy Noarov Soham Mallick Tao Wang Sunay Joshi Yan Sun Yangxinyu Xie Mengxin Yu Edgar Dobriban 36 0 0 25 May 2025
Spacetime Geometry of Denoising in Diffusion Models Rafał Karczewski Markus Heinonen Alison Pouplin Søren Hauberg Vikas Garg DiffM 63 0 0 23 May 2025
Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Zi Liang Haibo Hu Qingqing Ye Yaxin Xiao Ronghua Li AAML 97 1 0 19 May 2025
Variational Formulation of the Particle Flow Particle Filter Yinzhuang Yi Jorge Cortés Nikolay Atanasov 71 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 104 0 0 26 Apr 2025
Squared families: Searching beyond regular probability models Russell Tsuchida Jiawei Liu Cheng Soon Ong Dino Sejdinovic 68 0 0 27 Mar 2025
All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning Gokul Swamy Sanjiban Choudhury Wen Sun Zhiwei Steven Wu J. Andrew Bagnell OffRL 142 20 0 03 Mar 2025
Learning to Assist Humans without Inferring Rewards Vivek Myers Evan Ellis Sergey Levine Benjamin Eysenbach Anca Dragan 138 5 0 17 Jan 2025
Wasserstein Flow Matching: Generative modeling over families of distributions Doron Haviv Aram-Alexandre Pooladian Dana Peér Brandon Amos OOD 112 1 0 01 Nov 2024
New divergence measures between persistence diagrams and stability of vectorizations A. Bravetti Martin Mijangos P. Padilla 23 0 0 04 Oct 2024
Cartan moving frames and the data manifolds Eliot Tron Rita Fioresi Nicolas Couellan Stéphane Puechmorel 79 1 0 18 Sep 2024
Symplectic Bregman divergences Frank Nielsen 24 0 0 23 Aug 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 135 2 0 27 May 2024
Fisher Flow Matching for Generative Modeling over Discrete Data Oscar Davis Samuel Kessler Mircea Petrache .Ismail .Ilkan Ceylan Michael M. Bronstein A. Bose 111 21 0 23 May 2024
Sequential transport maps using SoS density estimation and $α$ -divergences Benjamin Zanger Tiangang Cui Martin Schreiber O. Zahm 70 1 0 27 Feb 2024
NCoder -- A Quantum Field Theory approach to encoding data David S. Berman Marc S. Klinger A. G. Stapleton AI4CE 81 2 0 01 Feb 2024
Divergences induced by dual subtractive and divisive normalizations of exponential families and their convex deformations Frank Nielsen 61 2 0 20 Dec 2023
Information geometry and $α$ -parallel prior of the beta-logistic distribution Lin Jiu Linyu Peng 53 0 0 17 Dec 2023
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion Junghyun Lee Se-Young Yun Kwang-Sung Jun 118 13 0 28 Oct 2023
Information Geometry for the Working Information Theorist Kumar Vijay Ashok Kumar Ieee Ting-Kam Leonard Member AI4CE 79 1 0 05 Oct 2023
Language Model Decoding as Direct Metrics Optimization Haozhe Ji Pei Ke Hongning Wang Minlie Huang 61 7 0 02 Oct 2023
The Fisher-Rao geometry of CES distributions Florent Bouchard A. Breloy Antoine Collas Alexandre Renaux G. Ginolhac 86 6 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 71 3 0 28 Jul 2023
Geometry in global coordinates in mechanics and optimal transport Du Nguyen OT 17 0 0 19 Jul 2023
Asymptotically Optimal Pure Exploration for Infinite-Armed Bandits Evelyn Xiao-Yue Gong Mark Sellke 94 1 0 03 Jun 2023
The Fisher Geometry and Geodesics of the Multivariate Normals, without Differential Geometry Brodie A. J. Lawson K. Burrage Kerrie Mengersen R. D. Santos 29 0 0 02 Jun 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 79 3 0 01 Jun 2023
Bayesian Renormalization D. Berman Marc S. Klinger A. G. Stapleton 92 17 0 17 May 2023
On Closed-Form Expressions for the Fisher-Rao Distance Henrique K. Miyamoto Fábio C. C. Meneghetti Julianna Pinele Sueli I. R. Costa 101 15 0 28 Apr 2023
Playing it safe: information constrains collective betting strategies P. Fleig V. Balasubramanian 55 0 0 18 Apr 2023
Codivergences and information matrices A. Derumigny Johannes Schmidt-Hieber 96 1 0 14 Mar 2023
Towards Optimal Compression: Joint Pruning and Quantization Ben Zandonati Glenn Bucagu Adrian Alan Pol M. Pierini Olya Sirkin Tal Kopetz MQ 81 3 0 15 Feb 2023
Phase2vec: Dynamical systems embedding with a physics-informed convolutional network Matthew Ricci Noa Moriel Zoe Piran Mor Nitzan AI4CE 101 5 0 07 Dec 2022
Properties of the Concrete distribution D. D. Chow 64 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 94 39 0 16 Oct 2022
FIT: A Metric for Model Sensitivity Ben Zandonati Adrian Alan Pol M. Pierini Olya Sirkin Tal Kopetz MQ 81 8 0 16 Oct 2022
Variational Representations of Annealing Paths: Bregman Information under Monotonic Embedding Rob Brekelmans Frank Nielsen 51 1 0 15 Sep 2022
Turning the information-sharing dial: efficient inference from different data sources Emily C. Hector Ryan Martin 61 6 0 18 Jul 2022
Unsupervised Learning Discriminative MIG Detectors in Nonhomogeneous Clutter Xiaoqiang Hua Yusuke Ono Linyu Peng Yuting Xu 19 27 0 24 Apr 2022
On the Kullback-Leibler divergence between pairwise isotropic Gaussian-Markov random fields A. Levada 13 2 0 24 Mar 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 97 25 0 20 Mar 2022
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality Xuhui Zhang Jose H. Blanchet Soumyadip Ghosh M. Squillante 65 9 0 23 Feb 2022
On a prior based on the Wasserstein information matrix W. Li F. Rubio 49 3 0 07 Feb 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 133 23 0 31 Jan 2022
Merging Models with Fisher-Weighted Averaging Michael Matena Colin Raffel FedML MoMe 107 403 0 18 Nov 2021
Geodesic curves in Gaussian random field manifolds A. Levada 21 0 0 06 Nov 2021
On the Importance of Firth Bias Reduction in Few-Shot Classification Saba Ghaffari Ehsan Saleh David A. Forsyth Yu-Xiong Wang 95 13 0 06 Oct 2021
Principal component analysis for Gaussian process posteriors Hideaki Ishibashi S. Akaho 123 6 0 15 Jul 2021
Fast approximations of the Jeffreys divergence between univariate Gaussian mixture models via exponential polynomial densities Frank Nielsen 101 12 0 13 Jul 2021
On the Variance of the Fisher Information for Deep Learning Alexander Soen Ke Sun FedML FAtt 71 18 0 09 Jul 2021