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Evan Archer
Evan Archer
Research Scientist, Sony AI
Bestätigte E-Mail-Adresse bei sony.com
Titel
Zitiert von
Zitiert von
Jahr
Linear dynamical neural population models through nonlinear embeddings
Y Gao, EW Archer, L Paninski, JP Cunningham
Advances in neural information processing systems 29, 2016
1952016
Black box variational inference for state space models
E Archer, IM Park, L Buesing, J Cunningham, L Paninski
arXiv preprint arXiv:1511.07367, 2015
1842015
Bayesian Entropy Estimation for Countable Discrete Distributions
E Archer, IM Park, JW Pillow
Journal of Machine Learning Research 15, 2833-2868, 2014
1132014
Low-dimensional models of neural population activity in sensory cortical circuits
E Archer, U Koster, JW Pillow, JH Macke
Advances in Neural Information Processing Systems, 343-351, 2014
792014
Spectral methods for neural characterization using generalized quadratic models
IM Park, E Archer, N Priebe, JW Pillow
Advances in Neural Information Processing Systems 26, 2454--2462, 2013
792013
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
A Speiser, J Yan, EW Archer, L Buesing, SC Turaga, JH Macke
Advances in neural information processing systems 30, 2017
642017
Bayesian and quasi-Bayesian estimators for mutual information from discrete data
E Archer, IM Park, JW Pillow
Entropy 15 (5), 1738-1755, 2013
532013
Bayesian entropy estimation for binary spike train data using parametric prior knowledge
E Archer, IM Park, JW Pillow
Advances in Neural Information Processing Systems 26, 1700--1708, 2013
432013
Bayesian estimation of discrete entropy with mixtures of stick-breaking priors
E Archer, IM Park, JW Pillow
Advances in Neural Information Processing Systems 25, 2024--2032, 2012
222012
Universal models for binary spike patterns using centered Dirichlet processes
IM Park, E Archer, K Latimer, JW Pillow
Advances in Neural Information Processing Systems 26, 2463--2471, 2013
162013
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents
J MacGlashan, E Archer, A Devlic, T Seno, C Sherstan, P Wurman, ...
arXiv preprint arXiv:2206.13901, 2022
92022
Scalable variational inference for super resolution microscopy
R Sun, E Archer, L Paninski
Artificial Intelligence and Statistics, 1057-1065, 2017
72017
Amortized inference for fast spike prediction from calcium imaging data
A Speiser, S Turaga, E Archer, JH Macke
Computational and Systems Neuroscience Meeting (COSYNE 2017), 207-208, 2017
2017
Canonical correlations reveal co-variability between spike trains and local field potentials in area MT
J Yates, E Archer, AC Huk, IM Park
BMC Neuroscience 16, 1-2, 2015
2015
Low Dimensional Dynamical Models of Neural Populations with Common Input
EW Archer, J Pillow, J Macke
15th Conference of Junior Neuroscientists of Tübingen (NeNa 2014): The …, 2014
2014
Low-dimensional dynamical neural population models with shared stimulus drive
EW Archer, JW Pillow, JH Macke
Bernstein Conference 2014, 72-73, 2014
2014
Low-dimensional models of neural population recordings with complex stimulus selectivity
EW Archer, JW Pillow, JH Macke
Computational and Systems Neuroscience Meeting (COSYNE 2014), 162-162, 2014
2014
Scalable nonparametric models for binary spike patterns
IM Park, EW Archer, K Latimer, JW Pillow
Computational and Systems Neuroscience Meeting (COSYNE 2014), 162-163, 2014
2014
Bayesian entropy estimators for spike trains
IM Park, E Archer, JW Pillow
BMC Neuroscience 14 (Suppl 1), P316, 2013
2013
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