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Liam Paninski

37 papers · 2006–2025 · 5 conferences · across top CS/AI conferences

Achievements

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+14 more ↓ 🧭 Keyword Pioneer 🌈 Renaissance Researcher (9) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (21) 🌍 Conference Polyglot (5)
πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🌈 Renaissance Researcher (9) 🌟 Keyword Trendsetter Combo (4) 🏠 Conference Loyalist (25) πŸ”¬ Deep Specialist (11) 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ’Ž Century Club (37) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (81) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (6)

Conferences

NIPS (25) AISTATS (5) ICML (5) ICLR (1) JMLR (1)

Papers

In vivo cell-type and brain region classification via multimodal contrastive learning ICLR 2025 Neural Encoding and Decoding at Scale ICML 2025 Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution NIPS 2024 Bayesian target optimisation for high-precision holographic optogenetics NIPS 2023 Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes NIPS 2023 Towards robust and generalizable representations of extracellular data using contrastive learning NIPS 2023 A general linear-time inference method for Gaussian Processes on one dimension JMLR 2021 Three-dimensional spike localization and improved motion correction for Neuropixels recordings NIPS 2021 Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking NIPS 2020 Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations NIPS 2020 Neural Clustering Processes ICML 2020 Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models NIPS 2019 Efficient characterization of electrically evoked responses for neural interfaces NIPS 2019 BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos NIPS 2019 Scalable approximate Bayesian inference for particle tracking data ICML 2018 Reparameterizing the Birkhoff Polytope for Variational Permutation Inference AISTATS 2018 Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems AISTATS 2017 Scalable Variational Inference for Super Resolution Microscopy AISTATS 2017 YASS: Yet Another Spike Sorter NIPS 2017 OnACID: Online Analysis of Calcium Imaging Data in Real Time NIPS 2017 Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons NIPS 2017 Stochastic Bouncy Particle Sampler ICML 2017 Fast Active Set Methods for Online Spike Inference from Calcium Imaging NIPS 2016 Partition Functions from Rao-Blackwellized Tempered Sampling ICML 2016 Linear dynamical neural population models through nonlinear embeddings NIPS 2016 Automated scalable segmentation of neurons from multispectral images NIPS 2016 Clustered factor analysis of multineuronal spike data NIPS 2014 Robust learning of low-dimensional dynamics from large neural ensembles NIPS 2013 Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions NIPS 2013 Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions NIPS 2013 Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits NIPS 2013 A multi-agent control framework for co-adaptation in brain-computer interfaces NIPS 2013 Low rank continuous-space graphical models AISTATS 2012 Fast interior-point inference in high-dimensional sparse, penalized state-space models AISTATS 2012 Information Rates and Optimal Decoding in Large Neural Populations NIPS 2011 Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds NIPS 2008 Real-time adaptive information-theoretic optimization of neurophysiology experiments NIPS 2006