Biswa Sengupta

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Imperial College London

Head of Machine Learning at Huawei Technologies since 2017, Visiting Senior Research Scientist at Imperial College London since 2016, Chief Research Scientist at Cortexica Vision Systems from 2016-2017, Senior Research Scientist at University of Cambridge 2016-2017, Research Scientist at University College London from 2011-2016, Research Scientist at Indian Institute of Science from 2011-2012, Research Scientist at LMU - Ludwig-Maximilians-Universität München from 2008-2011, Research Assistant at Hertie-Institute for Clinical Brain Research 2007, Research Assistant at Max Planck Institute for Biological Cybernetics from 2005-2007, Research Scientist at University of York 2004-2005, PhD in Computation and Neural Systems at University of Cambridge 2007-2011

Featured Co-authors

Vincent Dumoulin
22 publications
Kai Arulkumaran
20 publications
Antonia Creswell
17 publications
Karl Friston
15 publications
Anil A Bharath
15 publications
Alessandro Bay
11 publications
Aditya Singh
8 publications
Yu Qian
8 publications
Karl J. Friston
5 publications
Tom White
3 publications
Diogo S. Carvalho
3 publications

∙ 03/07/2022

Reinforcement Learning for Location-Aware Scheduling

Recent techniques in dynamical scheduling and resource management have f...

Stelios Stavroulakis, et al. ∙

∙ 03/07/2022

Learning to Ground Decentralized Multi-Agent Communication with Contrastive Learning

For communication to happen successfully, a common language is required ...

Yat Long Lo, et al. ∙

∙ 03/06/2022

Hierarchically Structured Scheduling and Execution of Tasks in a Multi-Agent Environment

In a warehouse environment, tasks appear dynamically. Consequently, a ta...

Diogo S. Carvalho, et al. ∙

∙ 06/17/2021

On the Dark Side of Calibration for Modern Neural Networks

Modern neural networks are highly uncalibrated. It poses a significant c...

Aditya Singh, et al. ∙

∙ 04/30/2018

How Robust are Deep Neural Networks?

Convolutional and Recurrent, deep neural networks have been successful i...

Biswa Sengupta, et al. ∙

∙ 11/14/2017

Conditional Autoencoders with Adversarial Information Factorization

Generative models, such as variational auto-encoders (VAE) and generativ...

Antonia Creswell, et al. ∙

∙ 11/08/2017

LatentPoison - Adversarial Attacks On The Latent Space

Robustness and security of machine learning (ML) systems are intertwined...

Antonia Creswell, et al. ∙

∙ 10/25/2017

GeoSeq2Seq: Information Geometric Sequence-to-Sequence Networks

The Fisher information metric is an important foundation of information ...

Alessandro Bay, et al. ∙

∙ 10/19/2017

Generative Adversarial Networks: An Overview

Generative adversarial networks (GANs) provide a way to learn deep repre...

Antonia Creswell, et al. ∙

∙ 10/11/2017

StackSeq2Seq: Dual Encoder Seq2Seq Recurrent Networks

A widely studied non-deterministic polynomial time (NP) hard problem lie...

Alessandro Bay, et al. ∙

∙ 10/11/2017

Sequence stacking using dual encoder Seq2Seq recurrent networks

A widely studied non-polynomial (NP) hard problem lies in finding a rout...

Alessandro Bay, et al. ∙

∙ 09/07/2017

Approximating meta-heuristics with homotopic recurrent neural networks

Much combinatorial optimisation problems constitute a non-polynomial (NP...

Alessandro Bay, et al. ∙

∙ 08/18/2017

Pillar Networks++: Distributed non-parametric deep and wide networks

In recent work, it was shown that combining multi-kernel based support v...

Biswa Sengupta, et al. ∙

∙ 07/21/2017

Multi-kernel learning of deep convolutional features for action recognition

Image understanding using deep convolutional network has reached human-l...

Biswa Sengupta, et al. ∙

∙ 05/20/2017

Bayesian Belief Updating of Spatiotemporal Seizure Dynamics

Epileptic seizure activity shows complicated dynamics in both space and ...

Gerald K Cooray, et al. ∙

∙ 05/17/2017

Approximate Bayesian inference as a gauge theory

In a published paper [Sengupta, 2016], we have proposed that the brain (...

Biswa Sengupta, et al. ∙