Paninski, Liam
- Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution
2024/07/19 by Yizi Zhang, Yanchen Wang, Zhang, Yizi +19 · 3 voices · 16 citations
#q-bio.NC #cs.LG #cs.NE
- Exact Hamiltonian Monte Carlo for Truncated Multivariate Gaussians
2012/08/20 by Pakman, Ari, Paninski, Liam · 7 citations
#Applications (stat.AP) #Computation (stat.CO) #FOS: Computer and information sciences
- Black box variational inference for state space models
2015/11/23 by Evan Archer, Il Memming Park, Archer, Evan +7 · 11 citations
Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Linear dynamical neural population models through nonlinear embeddings
2016/05/26 by Yuanjun Gao, Gao, Yuanjun, Evan Archer +5 · 7 citations
Neuroscience · Computer Science · #Neural dynamics and brain function #Neural Networks and Applications #Gaussian Processes and Bayesian Inference
- Recurrent switching linear dynamical systems
2016/10/26 by Scott W. Linderman, Linderman, Scott W., Andrew C. Miller +9 · 7 citations
Computer Science · Engineering · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Time Series Analysis and Forecasting
- Neural Encoding and Decoding at Scale
2025/04/11 by Yizi Zhang, Zhang, Yizi, Yanchen Wang +17 · 1 voice · 12 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial Intelligence (cs.AI) #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neurons and Cognition (q-bio.NC) #cs.AI #cs.LG #q-bio.NC
- Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary\n Distributions
2013/11/09 by Ari Pakman, Pakman, Ari, Liam Paninski +1 · 5 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Physical sciences #Markov Chains and Monte Carlo Methods #Statistical Mechanics (cond-mat.stat-mech) #Stochastic processes and statistical mechanics
- Amortized Probabilistic Detection of Communities in Graphs
2020/10/29 by Wang, Yueqi, Lee, Yoonho, Basu, Pallab +4 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- A structured matrix factorization framework for large scale calcium imaging data analysis
2014/09/09 by Pnevmatikakis, Eftychios A., Gao, Yuanjun, Soudry, Daniel +6 · 1 citation
#Applications (stat.AP) #FOS: Biological sciences #FOS: Computer and information sciences #Neurons and Cognition (q-bio.NC) #Quantitative Methods (q-bio.QM)
- Stochastic Bouncy Particle Sampler
2016/09/03 by Ari Pakman, Dar Gilboa, Pakman, Ari +5 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods
- Inpainting the Neural Picture: Inferring Unrecorded Brain Area Dynamics from Multi-Animal Datasets
2025/10/13 by Xia, Ji, Zhang, Yizi, Wang, Shuqi +4 · 2 citations
#Applications (stat.AP) #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (stat.ML) #Neurons and Cognition (q-bio.NC)
- Bayesian spike inference from calcium imaging data
2013/11/27 by Eftychios A. Pnevmatikakis, Pnevmatikakis, Eftychios A., Josh Merel +5 · 1 citation
Biochemistry, Genetics and Molecular Biology · Mathematics · Neuroscience · #Applications (stat.AP) #Diffusion and Search Dynamics #FOS: Biological sciences #FOS: Computer and information sciences #Markov Chains and Monte Carlo Methods #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Quantitative Methods (q-bio.QM)