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Siddharth Narayanaswamy

Dr

Siddharth Narayanaswamy BE PhD

Visiting Fellow

Biography

Siddharth N. (Sid) is a Reader (Associate Professor) in Explainable AI in the School of Informatics at the University of Edinburgh. Prior to this, he was a Senior Researcher in Engineering at the University of Oxford and a Postdoctoral Scholar in Psychology at Stanford.

He obtained his PhD from Purdue University in Electrical and Computer Engineering. His research broadly involves the confluence of machine learning, computer vision, natural-language processing, cognitive science, robotics, and elements of cognitive neuroscience, leading towards a central research goal to better understand perception and cognition with a view to enabling human-intelligible machine intelligence.

Personal Website

Most Recent Publications

Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models

Shi Y, Paige B, Torr PHS & Siddharth N (2020)

Capturing Label Characteristics in VAEs

Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)

Simulation-Based Inference for Global Health Decisions

Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)

DGPose: Deep Generative Models for Human Body Analysis

de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563

A Revised Generative Evaluation of Visual Dialogue

Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)

View all

Research Interests

  • Explainable AI
  • Human-Like Learning
  • Unsupervised Representation Learning
  • Approximate Probabilistic Inference
  • Probabilistic Programming

Related Academics

Most Recent Publications

Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models

Shi Y, Paige B, Torr PHS & Siddharth N (2020)

Capturing Label Characteristics in VAEs

Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)

Simulation-Based Inference for Global Health Decisions

Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)

DGPose: Deep Generative Models for Human Body Analysis

de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563

A Revised Generative Evaluation of Visual Dialogue

Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)

View all

Publications

Most Recent Publications

Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models

Shi Y, Paige B, Torr PHS & Siddharth N (2020)

Capturing Label Characteristics in VAEs

Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)

Simulation-Based Inference for Global Health Decisions

Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)

DGPose: Deep Generative Models for Human Body Analysis

de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563

A Revised Generative Evaluation of Visual Dialogue

Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)

View all

DPhil Opportunities

I take on 1-2 PhD students each year. Projects will broadly be on learning/using structured representations of perceptual data, and developing cutting-edge probabilistic inference tools to facilitate this.

Most Recent Publications

Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models

Shi Y, Paige B, Torr PHS & Siddharth N (2020)

Capturing Label Characteristics in VAEs

Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)

Simulation-Based Inference for Global Health Decisions

Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)

DGPose: Deep Generative Models for Human Body Analysis

de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563

A Revised Generative Evaluation of Visual Dialogue

Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)

View all