James Hensman - RankMe

77 papers A* 14A 11Journal 45Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ARO: A New Lens On Matrix Optimization For Large Models. CoRR Wenbo Gong, Javier Zazo, Qijun Luo, Puqian Wang, James Hensman, Chao Ma
2025	A*	`conf`	KBLaM: Knowledge Base augmented Language Model. ICLR Xi Wang, Taketomo Isazawa, Liana Mikaelyan, James Hensman
2025	J	`jnl`	OptRot: Mitigating Weight Outliers via Data-Free Rotations for Post-Training Quantization. CoRR Advait Gadhikar, Riccardo Grazzi, James Hensman
2025	—	`conf`	TurboAttention: Efficient attention approximation for high throughputs llm. MLSys Hao Kang, Srikant Bharadwaj, James Hensman, Tushar Krishna, Victor Rühle, Saravan Rajmohan
2024	J	`jnl`	KBLaM: Knowledge Base augmented Language Model. CoRR Xi Wang, Liana Mikaelyan, Taketomo Isazawa, James Hensman
2024	A*	`conf`	Learning to Extract Structured Entities Using Language Models. EMNLP Haolun Wu, Ye Yuan, Liana Mikaelyan, Alexander Meulemans, Xue Liu, James Hensman, Bhaskar Mitra
2024	J	`jnl`	Low-Rank Correction for Quantized LLMs. CoRR Meyer Scetbon, James Hensman
2024	J	`jnl`	Pyramid Vector Quantization for LLMs. CoRR Tycho F. A. van der Ouderaa, Maximilian L. Croci, Agrin Hilmkil, James Hensman
2024	A*	`conf`	QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs. NeurIPS Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Pashmina Cameron, Martin Jaggi, Dan Alistarh, Torsten Hoefler, James Hensman
2024	J	`jnl`	QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs. CoRR Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Martin Jaggi, Dan Alistarh, Torsten Hoefler, James Hensman
2024	A*	`conf`	SliceGPT: Compress Large Language Models by Deleting Rows and Columns. ICLR Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari Do Nascimento, Torsten Hoefler, James Hensman
2024	J	`jnl`	SliceGPT: Compress Large Language Models by Deleting Rows and Columns. CoRR Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari Do Nascimento, Torsten Hoefler, James Hensman
2024	J	`jnl`	Structured Entity Extraction Using Large Language Models. CoRR Haolun Wu, Ye Yuan, Liana Mikaelyan, Alexander Meulemans, Xue Liu, James Hensman, Bhaskar Mitra
2024	J	`jnl`	TurboAttention: Efficient Attention Approximation For High Throughputs LLMs. CoRR Hao Kang, Srikant Bharadwaj, James Hensman, Tushar Krishna, Victor Rühle, Saravan Rajmohan
2023	J	`jnl`	KBFormer: A Diffusion Model for Structured Entity Completion. CoRR Ouail Kitouni, Niklas Nolte, James Hensman, Bhaskar Mitra
2023	J	`jnl`	Sparse Gaussian Processes with Spherical Harmonic Features Revisited. CoRR Stefanos Eleftheriadis, Dominic Richards, James Hensman
2022	A*	`conf`	Additive Gaussian Processes Revisited. ICML Xiaoyu Lu, Alexis Boukouvalas, James Hensman
2022	J	`jnl`	Additive Gaussian Processes Revisited. CoRR Xiaoyu Lu, Alexis Boukouvalas, James Hensman
2021	A*	`conf`	Deep Neural Networks as Point Estimates for Deep Gaussian Processes. NeurIPS Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
2021	J	`jnl`	Deep Neural Networks as Point Estimates for Deep Gaussian Processes. CoRR Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
2021	J	`jnl`	GPflux: A Library for Deep Gaussian Processes. CoRR Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John
2021	J	`jnl`	Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments. Bioinform. Nuha Bintayyash, Sokratia Georgaka, S. T. John, Sumon Ahmed, Alexis Boukouvalas, James Hensman, Magnus Rattray
2020	J	`jnl`	A Framework for Interdomain and Multioutput Gaussian Processes. CoRR Mark van der Wilk, Vincent Dutordoir, S. T. John, Artem Artemev, Vincent Adam, James Hensman
2020	A	`conf`	Amortized variance reduction for doubly stochastic objective. UAI Ayman Boustati, Sattar Vakili, James Hensman, S. T. John
2020	J	`jnl`	Amortized variance reduction for doubly stochastic objectives. CoRR Ayman Boustati, Sattar Vakili, James Hensman, S. T. John
2020	A	`conf`	Bayesian Image Classification with Deep Convolutional Gaussian Processes. AISTATS Vincent Dutordoir, Mark van der Wilk, Artem Artemev, James Hensman
2020	A	`conf`	Doubly Sparse Variational Gaussian Processes. AISTATS Vincent Adam, Stefanos Eleftheriadis, Artem Artemev, Nicolas Durrande, James Hensman
2020	J	`jnl`	Doubly Sparse Variational Gaussian Processes. CoRR Vincent Adam, Stefanos Eleftheriadis, Nicolas Durrande, Artem Artemev, James Hensman
2020	A*	`conf`	Sparse Gaussian Processes with Spherical Harmonic Features. ICML Vincent Dutordoir, Nicolas Durrande, James Hensman
2020	J	`jnl`	Sparse Gaussian Processes with Spherical Harmonic Features. CoRR Vincent Dutordoir, Nicolas Durrande, James Hensman
2019	A	`conf`	Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era. AISTATS Nicolas Durrande, Vincent Adam, Lucas Bordeaux, Stefanos Eleftheriadis, James Hensman
2019	J	`jnl`	Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era. CoRR Nicolas Durrande, Vincent Adam, Lucas Bordeaux, Stefanos Eleftheriadis, James Hensman
2019	A*	`conf`	Deep Gaussian Processes with Importance-Weighted Variational Inference. ICML Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
2019	J	`jnl`	Deep Gaussian Processes with Importance-Weighted Variational Inference. CoRR Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
2019	A*	`conf`	Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models. ICML Alessandro Davide Ialongo, Mark van der Wilk, James Hensman, Carl Edward Rasmussen
2019	J	`jnl`	Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models. CoRR Alessandro Davide Ialongo, Mark van der Wilk, James Hensman, Carl Edward Rasmussen
2019	A*	`conf`	Pseudo-Extended Markov chain Monte Carlo. NeurIPS Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone, James Hensman
2019	J	`jnl`	Translation Insensitivity for Deep Convolutional Gaussian Processes. CoRR Vincent Dutordoir, Mark van der Wilk, Artem Artemev, Marcin Tomczak, James Hensman
2019	—	`conf`	Variational Gaussian Process Models without Matrix Inverses. AABI Mark van der Wilk, S. T. John, Artem Artemev, James Hensman
2018	A*	`conf`	Gaussian Process Conditional Density Estimation. NeurIPS Vincent Dutordoir, Hugh Salimbeni, James Hensman, Marc Peter Deisenroth
2018	J	`jnl`	Gaussian Process Conditional Density Estimation. CoRR Vincent Dutordoir, Hugh Salimbeni, Marc Peter Deisenroth, James Hensman
2018	A*	`conf`	Infinite-Horizon Gaussian Processes. NeurIPS Arno Solin, James Hensman, Richard E. Turner
2018	J	`jnl`	Infinite-Horizon Gaussian Processes. CoRR Arno Solin, James Hensman, Richard E. Turner
2018	A*	`conf`	Large-Scale Cox Process Inference using Variational Fourier Features. ICML S. T. John, James Hensman
2018	J	`jnl`	Large-Scale Cox Process Inference using Variational Fourier Features. CoRR S. T. John, James Hensman
2018	A*	`conf`	Learning Invariances using the Marginal Likelihood. NeurIPS Mark van der Wilk, Matthias Bauer, S. T. John, James Hensman
2018	J	`jnl`	Learning Invariances using the Marginal Likelihood. CoRR Mark van der Wilk, Matthias Bauer, S. T. John, James Hensman
2018	A	`conf`	Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models. AISTATS Hugh Salimbeni, Stefanos Eleftheriadis, James Hensman
2018	J	`jnl`	Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models. CoRR Hugh Salimbeni, Stefanos Eleftheriadis, James Hensman
2018	J	`jnl`	Non-Factorised Variational Inference in Dynamical Systems. CoRR Alessandro Davide Ialongo, Mark van der Wilk, James Hensman, Carl Edward Rasmussen
2018	J	`jnl`	Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction. IEEE Trans. Pattern Anal. Mach. Intell. Hossein Soleimani, James Hensman, Suchi Saria
2017	—	`conf`	Convolutional Gaussian Processes. NIPS Mark van der Wilk, Carl Edward Rasmussen, James Hensman
2017	J	`jnl`	Convolutional Gaussian Processes. CoRR Mark van der Wilk, Carl Edward Rasmussen, James Hensman
2017	J	`jnl`	GPflow: A Gaussian Process Library using TensorFlow. J. Mach. Learn. Res. Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson, Keisuke Fujii, Alexis Boukouvalas, Pablo León-Villagrá, Zoubin Ghahramani, James Hensman
2017	—	`conf`	Identification of Gaussian Process State Space Models. NIPS Stefanos Eleftheriadis, Tom Nicholson, Marc Peter Deisenroth, James Hensman
2017	J	`jnl`	Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction. CoRR Hossein Soleimani, James Hensman, Suchi Saria
2017	J	`jnl`	Variational Fourier Features for Gaussian Processes. J. Mach. Learn. Res. James Hensman, Nicolas Durrande, Arno Solin
2016	A	`conf`	Chained Gaussian Processes. AISTATS Alan D. Saul, James Hensman, Aki Vehtari, Neil D. Lawrence
2016	J	`jnl`	Chained Gaussian Processes. CoRR Alan D. Saul, James Hensman, Aki Vehtari, Neil D. Lawrence
2016	J	`jnl`	Detecting periodicities with Gaussian processes. PeerJ Comput. Sci. Nicolas Durrande, James Hensman, Magnus Rattray, Neil D. Lawrence
2016	J	`jnl`	Detecting periodicities with Gaussian processes. PeerJ Prepr. Nicolas Durrande, James Hensman, Magnus Rattray, Neil D. Lawrence
2016	A	`conf`	On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes. AISTATS Alexander G. de G. Matthews, James Hensman, Richard E. Turner, Zoubin Ghahramani
2016	—	`conf`	Scalable transformed additive signal decomposition by non-conjugate Gaussian process inference. MLSP Vincent Adam, James Hensman, Maneesh Sahani
2015	J	`jnl`	Fast Nonparametric Clustering of Structured Time-Series. IEEE Trans. Pattern Anal. Mach. Intell. James Hensman, Magnus Rattray, Neil D. Lawrence
2015	J	`jnl`	Fast and accurate approximate inference of transcript expression from RNA-seq data. Bioinform. James Hensman, Panagiotis Papastamoulis, Peter Glaus, Antti Honkela, Magnus Rattray
2015	—	`conf`	MCMC for Variationally Sparse Gaussian Processes. NIPS James Hensman, Alexander G. de G. Matthews, Maurizio Filippone, Zoubin Ghahramani
2015	A	`conf`	Scalable Variational Gaussian Process Classification. AISTATS James Hensman, Alexander G. de G. Matthews, Zoubin Ghahramani
2015	J	`jnl`	Spike and Slab Gaussian Process Latent Variable Models. CoRR Zhenwen Dai, James Hensman, Neil D. Lawrence
2014	J	`jnl`	Fast variational inference for nonparametric clustering of structured time-series. CoRR James Hensman, Magnus Rattray, Neil D. Lawrence
2014	J	`jnl`	Gaussian Process Models with Parallelization and GPU acceleration. CoRR Zhenwen Dai, Andreas C. Damianou, James Hensman, Neil D. Lawrence
2014	A	`conf`	Hybrid Discriminative-Generative Approach with Gaussian Processes. AISTATS Ricardo Andrade Pacheco, James Hensman, Max Zwiessele, Neil D. Lawrence
2014	A	`conf`	Tilted Variational Bayes. AISTATS James Hensman, Max Zwiessele, Neil D. Lawrence
2013	A	`conf`	Gaussian Processes for Big Data. UAI James Hensman, Nicoló Fusi, Neil D. Lawrence
2013	J	`jnl`	Gaussian Processes for Big Data. CoRR James Hensman, Nicoló Fusi, Neil D. Lawrence
2013	J	`jnl`	Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters. BMC Bioinform. James Hensman, Neil D. Lawrence, Magnus Rattray
2012	J	`jnl`	Fast Variational Inference in the Conjugate Exponential Family CoRR James Hensman, Magnus Rattray, Neil D. Lawrence
2012	—	`conf`	Fast Variational Inference in the Conjugate Exponential Family. NIPS James Hensman, Magnus Rattray, Neil D. Lawrence