Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE

9 November 2020

Papers citing "Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE"

39 / 39 papers shown

Title
POCO: Scalable Neural Forecasting through Population Conditioning Yu Duan Hamza Tahir Chaudhry Misha B. Ahrens Christopher D Harvey Matthew G Perich Karl Deisseroth Kanaka Rajan AI4CE 10 0 0 17 Jun 2025
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research Patrik Reizinger Randall Balestriero David Klindt Wieland Brendel 186 1 0 17 Apr 2025
A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement Chengrui Li Yunmiao Wang Yule Wang Weihan Li Dieter Jaeger Anqi Wu CoGe DRL 134 1 0 04 Feb 2025
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks Junyan Li Bin Hu Z. Guan 182 0 0 30 Jan 2025
Single-neuron deep generative model uncovers underlying physics of neuronal activity in Ca imaging data Jordi Abante Angelo Piga Berta Ros Clara F López-León Josep Canals Jordi Soriano SyDa 105 0 0 24 Jan 2025
Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors Finn Schmidt Suhas Shrinivasan Polina Turishcheva Fabian H. Sinz 169 1 0 21 Oct 2024
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models Yule Wang Chengrui Li Weihan Li Anqi Wu DiffM 90 6 0 12 Oct 2024
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation Zhengrui Guo F. Zhou Wei Wu Qichen Sun Lishuang Feng Jinzhuo Wang Hao Chen 88 2 0 02 Oct 2024
Graph-Based Representation Learning of Neuronal Dynamics and Behavior M. Khajehnejad Forough Habibollahi Ahmad Khajehnejad Chris French Brett J. Kagan Adeel Razi 89 1 0 01 Oct 2024
Diffusion-Based Generation of Neural Activity from Disentangled Latent Codes Jonathan D. McCart Andrew R. Sedler Christopher Versteeg Domenick M. Mifsud Mattia Rigotti-Thompson C. Pandarinath DiffM SyDa 71 1 0 30 Jul 2024
NeuroBind: Towards Unified Multimodal Representations for Neural Signals Fengyu Yang Chao Feng Daniel Wang Tianye Wang Ziyao Zeng ... Hyoungseob Park Pengliang Ji Han Zhao Yuanning Li Alex Wong 110 9 0 19 Jul 2024
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models Jaehoon Hahm Junho Lee Sunghyun Kim Joonseok Lee DiffM 76 11 0 16 Jul 2024
Latent Diffusion for Neural Spiking Data J. Kapoor Auguste Schulz Julius Vetter Felix Pei Richard Gao Jakob H. Macke DiffM 59 3 0 27 Jun 2024
Inferring stochastic low-rank recurrent neural networks from neural data Matthijs Pals A Erdem Sağtekin Felix Pei Manuel Gloeckler Jakob H Macke 563 7 0 24 Jun 2024
Shaping History: Advanced Machine Learning Techniques for the Analysis and Dating of Cuneiform Tablets over Three Millennia Danielle Kapon Michael Fire S. Gordin 107 1 0 06 Jun 2024
A theory of neural emulators C. Mitelut 60 0 0 22 May 2024
Predictive variational autoencoder for learning robust representations of time-series data Julia Huiming Wang Dexter Tsin Tatiana Engel CML OOD AI4TS 75 2 0 12 Dec 2023
Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data Antonis Antoniades Yiyi Yu Joseph Canzano William Wang Spencer L. Smith AI4CE 107 13 0 31 Oct 2023
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data Rabia Gondur Usama Bin Sikandar Evan Schaffer Mikio C. Aoi Stephen L. Keeley DRL 47 9 0 04 Oct 2023
Learning multi-modal generative models with permutation-invariant encoders and tighter variational bounds Marcel Hirt Domenico Campolo Victoria Leong Juan-Pablo Ortega DRL 71 0 0 01 Sep 2023
Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data Cheol Jun Cho Edward F. Chang Gopala K. Anumanchipalli 71 7 0 12 Aug 2023
Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes Gehua (Marcus) Ma Runhao Jiang Rui Yan Huajin Tang AI4TS 72 7 0 21 Jun 2023
Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models Yule Wang Zijing Wu Chengrui Li Anqi Wu DiffM 111 12 0 09 Jun 2023
Interpretable statistical representations of neural population dynamics and geometry Adam Gosztolai Robert L. Peach Alexis Arnaudon Mauricio Barahona P. Vandergheynst 66 10 0 06 Apr 2023
Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning Aapo Hyvarinen Ilyes Khemakhem H. Morioka CML OOD 106 37 0 29 Mar 2023
Concept Algebra for (Score-Based) Text-Controlled Generative Models Zihao Wang Lin Gui Jeffrey Negrea Victor Veitch CoGe DiffM 88 41 0 07 Feb 2023
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics Manuela Brenner Florian Hess G. Koppe Daniel Durstewitz 278 11 0 15 Dec 2022
Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles Martin Bjerke Lukas Schott Kristopher T. Jensen Claudia Battistin David A. Klindt Benjamin A. Dunn 68 7 0 06 Oct 2022
Fair Inference for Discrete Latent Variable Models Rashidul Islam Shimei Pan James R. Foulds FaML 82 1 0 15 Sep 2022
Indeterminacy in Generative Models: Characterization and Strong Identifiability Quanhan Xi Benjamin Bloem-Reddy 90 27 0 02 Jun 2022
Learnable latent embeddings for joint behavioral and neural analysis Steffen Schneider Jin Hwa Lee Mackenzie W. Mathis 121 231 0 01 Apr 2022
Covariate-informed Representation Learning to Prevent Posterior Collapse of iVAE Young-geun Kim Yang Liu Xue Wei OOD CML 83 1 0 09 Feb 2022
Reproducible, incremental representation learning with Rosetta VAE Miles Martinez John M. Pearson DRL 23 1 0 13 Jan 2022
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity Ran Liu Mehdi Azabou M. Dabagia Chi-Heng Lin M. G. Azar Keith B. Hengen Michal Valko Eva L. Dyer OCL SSL DRL 61 37 0 03 Nov 2021
Identifiable Deep Generative Models via Sparse Decoding Gemma E. Moran Dhanya Sridhar Yixin Wang David M. Blei BDL 107 49 0 20 Oct 2021
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity Felix Pei Joel Ye D. Zoltowski Anqi Wu Raeed H. Chowdhury ... L. Miller Jonathan W. Pillow Il Memming Park Eva L. Dyer C. Pandarinath 296 90 0 09 Sep 2021
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA Hermanni Hälvä Sylvain Le Corff Luc Lehéricy Jonathan So Yongjie Zhu Elisabeth Gassiat Aapo Hyvarinen CML 62 65 0 17 Jun 2021
Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction Mehdi Azabou M. G. Azar Ran Liu Chi-Heng Lin Erik C. Johnson ... Lindsey Kitchell Keith B. Hengen William R. Gray Roncal Michal Valko Eva L. Dyer AI4TS 85 57 0 19 Feb 2021
Building population models for large-scale neural recordings: opportunities and pitfalls C. Hurwitz N. Kudryashova A. Onken Matthias H Hennig 73 39 0 03 Feb 2021