Classification and Geometry of General Perceptual Manifolds

17 October 2017

Papers citing "Classification and Geometry of General Perceptual Manifolds"

25 / 25 papers shown

Title
What's Inside Your Diffusion Model? A Score-Based Riemannian Metric to Explore the Data Manifold Simone Azeglio Arianna Di Bernardo DiffM 29 0 0 16 May 2025
The Geometry of Tokens in Internal Representations of Large Language Models Karthik Viswanathan Yuri Gardinazzi Giada Panerai Alberto Cazzaniga Matteo Biagetti AIFin 102 4 0 17 Jan 2025
Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample Matrices Chanwoo Chun SueYeon Chung Daniel D. Lee 34 1 0 23 Oct 2024
Geometric Signatures of Compositionality Across a Language Model's Lifetime Jin Hwa Lee Thomas Jiralerspong Lei Yu Yoshua Bengio Emily Cheng CoGe 87 1 0 02 Oct 2024
Emergence of a High-Dimensional Abstraction Phase in Language Transformers Emily Cheng Diego Doimo Corentin Kervadec Iuri Macocco Jade Yu Alessandro Laio Marco Baroni 112 11 0 24 May 2024
Restoring balance: principled under/oversampling of data for optimal classification Emanuele Loffredo Mauro Pastore Simona Cocco R. Monasson 43 9 0 15 May 2024
Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language Eghbal A. Hosseini Evelina Fedorenko LLMSV 28 4 0 05 Nov 2023
Neural Sampling in Hierarchical Exponential-family Energy-based Models Xingsi Dong Si Wu 38 3 0 12 Oct 2023
Data Representations' Study of Latent Image Manifolds Ilya Kaufman Omri Azencot 14 7 0 31 May 2023
Mapping of attention mechanisms to a generalized Potts model Riccardo Rende Federica Gerace Alessandro Laio Sebastian Goldt 19 22 0 14 Apr 2023
Inversion dynamics of class manifolds in deep learning reveals tradeoffs underlying generalisation Simone Ciceri Lorenzo Cassani Matteo Osella P. Rotondo P. Pizzochero M. Gherardi 41 7 0 09 Mar 2023
Neural networks learn to magnify areas near decision boundaries Jacob A. Zavatone-Veth Sheng Yang Julian Rubinfien Cengiz Pehlevan MLT AI4CE 28 6 0 26 Jan 2023
Linear Classification of Neural Manifolds with Correlated Variability Albert J. Wakhloo Tamara J. Sussman SueYeon Chung 29 10 0 27 Nov 2022
Analyzing Data-Centric Properties for Graph Contrastive Learning Puja Trivedi Ekdeep Singh Lubana Mark Heimann Danai Koutra Jayaraman J. Thiagarajan 30 11 0 04 Aug 2022
Investigating Power laws in Deep Representation Learning Arna Ghosh Arnab Kumar Mondal Kumar Krishna Agrawal Blake A. Richards SSL OOD 14 19 0 11 Feb 2022
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception Joel Dapello J. Feather Hang Le Tiago Marques David D. Cox Josh H. McDermott J. DiCarlo SueYeon Chung AAML OOD 19 25 0 12 Nov 2021
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? M. Farrell Blake Bordelon Shubhendu Trivedi Cengiz Pehlevan 18 5 0 14 Oct 2021
Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks Landan Seguin A. Ndirango Neeli Mishra SueYeon Chung Tyler Lee OOD 25 2 0 26 Aug 2021
Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models Matteo Alleman J. Mamou Miguel Rio Hanlin Tang Yoon Kim SueYeon Chung NAI 38 17 0 15 Apr 2021
The Gaussian equivalence of generative models for learning with shallow neural networks Sebastian Goldt Bruno Loureiro Galen Reeves Florent Krzakala M. Mézard Lenka Zdeborová BDL 41 100 0 25 Jun 2020
Untangling in Invariant Speech Recognition Cory Stephenson J. Feather Suchismita Padhy Oguz H. Elibol Hanlin Tang Josh H. McDermott SueYeon Chung SSL 30 30 0 03 Mar 2020
Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future Grace W. Lindsay MedIm 35 424 0 20 Jan 2020
Modelling the influence of data structure on learning in neural networks: the hidden manifold model Sebastian Goldt M. Mézard Florent Krzakala Lenka Zdeborová BDL 29 51 0 25 Sep 2019
Dimensionality compression and expansion in Deep Neural Networks Stefano Recanatesi M. Farrell Madhu S. Advani Timothy Moore Guillaume Lajoie E. Shea-Brown 26 72 0 02 Jun 2019
Analyzing biological and artificial neural networks: challenges with opportunities for synergy? David Barrett Ari S. Morcos Jakob H. Macke AI4CE 25 110 0 31 Oct 2018