Biswa Sengupta
Biswa Sengupta
Imperial College London, University College London
Verified email at - Homepage
Cited by
Cited by
Generative Adversarial Networks: An Overview
A Creswell, T White, V Dumoulin, K Arulkumaran, B Sengupta, ...
IEEE Signal Processing Magazine, 2018
Knowing one's place: a free-energy approach to pattern regulation
K Friston, M Levin, B Sengupta, G Pezzulo
Journal of the Royal Society Interface 12 (105), 20141383, 2015
Action potential energy efficiency varies among neuron types in vertebrates and invertebrates
B Sengupta, M Stemmler, SB Laughlin, JE Niven
PLoS computational biology 6 (7), e1000840, 2010
Information and efficiency in the nervous system—a synthesis
B Sengupta, MB Stemmler, KJ Friston
PLoS computational biology 9 (7), e1003157, 2013
Towards a neuronal gauge theory
B Sengupta, A Tozzi, GK Cooray, PK Douglas, KJ Friston
PLoS Biology 14 (3), e1002400, 2016
Power consumption during neuronal computation
B Sengupta, MB Stemmler
Proceedings of the IEEE 102 (5), 738-750, 2014
Cognitive dynamics: From attractors to active inference
K Friston, B Sengupta, G Auletta
Proceedings of the IEEE 102 (4), 427-445, 2014
Balanced excitatory and inhibitory synaptic currents promote efficient coding and metabolic efficiency
B Sengupta, SB Laughlin, JE Niven
PLoS computational biology 9 (10), e1003263, 2013
The effect of cell size and channel density on neuronal information encoding and energy efficiency
B Sengupta, AA Faisal, SB Laughlin, JE Niven
Journal of Cerebral Blood Flow & Metabolism 33 (9), 1465-1473, 2013
Efficient gradient computation for dynamical models
B Sengupta, KJ Friston, WD Penny
NeuroImage 98, 521-527, 2014
Consequences of converting graded to action potentials upon neural information coding and energy efficiency
B Sengupta, SB Laughlin, JE Niven
PLoS computational biology 10 (1), e1003439, 2014
Ten simple rules for effective computational research
JM Osborne, MO Bernabeu, M Bruna, B Calderhead, J Cooper, ...
PLoS Computational Biology 10 (3), e1003506, 2014
Gradient-based MCMC samplers for dynamic causal modelling
B Sengupta, KJ Friston, WD Penny
NeuroImage 125, 1107-1118, 2016
Comparison of Langevin and Markov channel noise models for neuronal signal generation
B Sengupta, SB Laughlin, JE Niven
Physical Review E 81 (1), 011918, 2010
Neural dynamics under active inference: Plausibility and efficiency of information processing
L Da Costa, T Parr, B Sengupta, K Friston
Entropy 23 (4), 454, 2021
Hemispheric brain asymmetry differences in youths with attention-deficit/hyperactivity disorder
PK Douglas, B Gutman, A Anderson, C Larios, KE Lawrence, K Narr, ...
NeuroImage: Clinical 18, 744-752, 2018
Adversarial information factorization
A Creswell, Y Mohamied, B Sengupta, AA Bharath
arXiv preprint arXiv:1711.05175, 2017
Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating
GK Cooray, B Sengupta, PK Douglas, K Friston
Neuroimage 125, 1142-1154, 2016
Characterising seizures in anti-NMDA-receptor encephalitis with dynamic causal modelling
GK Cooray, B Sengupta, P Douglas, M Englund, R Wickstrom, K Friston
Neuroimage 118, 508-519, 2015
Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents
AM Chagas, L Theis, B Sengupta, MC Stüttgen, M Bethge, C Schwarz
Frontiers in Neural Circuits 7, 190, 2013
The system can't perform the operation now. Try again later.
Articles 1–20