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James Hensman

30 papers · 2012–2025 · 7 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+7 more ↓ πŸ—ΊοΈ Taxonomy Completionist (39) πŸƒ Academic Marathon Β· Half 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
πŸ”¬ Deep Specialist (19) πŸ† Keyword Champion (2) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable Β· Bronze ⚑ Prolific Year Β· Productive πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (111)

Venues

NeurIPS (10) AISTATS (9) ICML (5) ICLR (2) JMLR (2) EMNLP (1) UAI (1)

Top co-authors

Nicolas Durrande (5) Vincent Dutordoir (5) Zoubin Ghahramani (5) Mark van der Wilk (5) Stefanos Eleftheriadis (4) Neil D. Lawrence (4) Marc Deisenroth (3) ST John (3) Hugh Salimbeni (3) Torsten Hoefler (2)

Research topics

Machine Learning (27) Optimization & Theory (22) Artificial Intelligence (17) Bayesian & Probabilistic Β· Machine Learning (16) Bayesian & Probabilistic Β· Artificial Intelligence (13) Deep Learning (11) Core Methods (10) Models (8) Core AI (4) Mathematics & Optimization (3) Natural Language Processing (3) Application Areas (2) Applications (2) Learning Types (2) Optimization (2)

Keywords

variational inference (21) gaussian process (19) sparse approximation (6) marginal likelihood (5) posterior approximation (4) inducing point (4) approximate inference (3) bayesian inference (3) deep gaussian process (3) state space model (3) automatic differentiation (3) gaussian processes (2) additive model (2) hyperparameter learning (2) fourier feature (2) convolutional kernel (2) stochastic optimization (2) markov chain monte carlo (2) image classification (2) uncertainty quantification (2)

Papers

KBLaM: Knowledge Base augmented Language Model ICLR 2025 Learning to Extract Structured Entities Using Language Models EMNLP 2024 QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs NeurIPS 2024 SliceGPT: Compress Large Language Models by Deleting Rows and Columns ICLR 2024 Additive Gaussian Processes Revisited ICML 2022 Deep Neural Networks as Point Estimates for Deep Gaussian Processes NeurIPS 2021 Amortized variance reduction for doubly stochastic objective UAI 2020 Bayesian Image Classification with Deep Convolutional Gaussian Processes AISTATS 2020 Doubly Sparse Variational Gaussian Processes AISTATS 2020 Sparse Gaussian Processes with Spherical Harmonic Features ICML 2020 Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019 Deep Gaussian Processes with Importance-Weighted Variational Inference ICML 2019 Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models ICML 2019 Pseudo-Extended Markov chain Monte Carlo NeurIPS 2019 Gaussian Process Conditional Density Estimation NeurIPS 2018 Infinite-Horizon Gaussian Processes NeurIPS 2018 Large-Scale Cox Process Inference using Variational Fourier Features ICML 2018 Learning Invariances using the Marginal Likelihood NeurIPS 2018 Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models AISTATS 2018 Variational Fourier Features for Gaussian Processes JMLR 2018 Convolutional Gaussian Processes NeurIPS 2017 GPflow: A Gaussian Process Library using TensorFlow JMLR 2017 Identification of Gaussian Process State Space Models NeurIPS 2017 Chained Gaussian Processes AISTATS 2016 On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes AISTATS 2016 MCMC for Variationally Sparse Gaussian Processes NeurIPS 2015 Scalable Variational Gaussian Process Classification AISTATS 2015 Hybrid Discriminative-Generative Approach with Gaussian Processes AISTATS 2014 Tilted Variational Bayes AISTATS 2014 Fast Variational Inference in the Conjugate Exponential Family NeurIPS 2012