Zhenwen Dai

According to our database, Zhenwen Dai authored at least 44 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

In-context Exploration-Exploitation for Reinforcement Learning.

Zhenwen Dai, Federico Tomasi, Sina Ghiassian

CoRR, 2024

2023

Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics.

Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang

J. Mach. Learn. Res., 2023

A Strong Baseline for Batch Imitation Learning.

Matthew Smith, Lucas Maystre, Zhenwen Dai, Kamil Ciosek

CoRR, 2023

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning.

Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Exploiting Sequential Music Preferences via Optimisation-Based Sequencing.

Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

The ELBO of Variational Autoencoders Converges to a Sum of Entropies.

Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Efficient inference for dynamic topic modeling with large vocabularies.

Federico Tomasi, Mounia Lalmas, Zhenwen Dai

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Making Differentiable Architecture Search less local.

Erik Bodin, Federico Tomasi, Zhenwen Dai

CoRR, 2021

Black-box density function estimation using recursive partitioning.

Erik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Data-Driven Mode Identification and Unsupervised Fault Detection for Nonlinear Multimode Processes.

Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan

IEEE Trans. Ind. Informatics, 2020

The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies.

Jörg Lücke, Dennis Forster, Zhenwen Dai

CoRR, 2020

Black-box density function estimation using recursive partitioning.

Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek

CoRR, 2020

Stochastic Variational Inference for Dynamic Correlated Topic Models.

Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Model Selection for Production System via Automated Online Experiments.

Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Benjamin A. Carterette, Mounia Lalmas

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Modulating Surrogates for Bayesian Optimization.

Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds.

Abdul-Saboor Sheikh, Nicol S. Harper, Jakob Drefs, Yosef Singer, Zhenwen Dai, Richard E. Turner, Jörg Lücke

PLoS Comput. Biol., 2019

ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions.

Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke

CoRR, 2019

A probabilistic principal component analysis-based approach in process monitoring and fault diagnosis with application in wastewater treatment plant.

Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan

Appl. Soft Comput., 2019

Meta-Surrogate Benchmarking for Hyperparameter Optimization.

Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variational Information Distillation for Knowledge Transfer.

Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Intrinsic Gaussian processes on complex constrained domains.

Mu Niu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil D. Lawrence, David B. Dunson

CoRR, 2018

Structured Variationally Auto-encoded Optimization.

Xiaoyu Lu, Javier González, Zhenwen Dai, Neil D. Lawrence

Proceedings of the 35th International Conference on Machine Learning, 2018

Truncated Variational Sampling for 'Black Box' Optimization of Generative Models.

Jörg Lücke, Zhenwen Dai, Georgios Exarchakis

Proceedings of the Latent Variable Analysis and Signal Separation, 2018

2017

GP-Select: Accelerating EM Using Adaptive Subspace Preselection.

Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton

Neural Comput., 2017

Auto-Differentiating Linear Algebra.

Matthias W. Seeger, Asmus Hetzel, Zhenwen Dai, Neil D. Lawrence

CoRR, 2017

Efficient inference for sparse latent variable models of transcriptional regulation.

Zhenwen Dai, Mudassar Iqbal, Neil D. Lawrence, Magnus Rattray

Bioinform., 2017

Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes.

Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Preferential Bayesian Optimization.

Javier González, Zhenwen Dai, Andreas C. Damianou, Neil D. Lawrence

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Data-Driven Detection of Prominent Objects.

José A. Rodríguez-Serrano, Diane Larlus, Zhenwen Dai

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model.

Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek, Neil D. Lawrence

CoRR, 2016

Recurrent Gaussian Processes.

César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence

Proceedings of the 4th International Conference on Learning Representations, 2016

Variational Auto-encoded Deep Gaussian Processes.

Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence

Proceedings of the 4th International Conference on Learning Representations, 2016

Batch Bayesian Optimization via Local Penalization.

Javier González, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Spike and Slab Gaussian Process Latent Variable Models.

Zhenwen Dai, James Hensman, Neil D. Lawrence

CoRR, 2015

2014

Autonomous Document Cleaning - A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts.

Zhenwen Dai, Jörg Lücke

IEEE Trans. Pattern Anal. Mach. Intell., 2014

Gaussian Process Models with Parallelization and GPU acceleration.

Zhenwen Dai, Andreas C. Damianou, James Hensman, Neil D. Lawrence

CoRR, 2014

2013

Unsupervised learning of invariant object representations: a probabilistic generative modeling approach.

Zhenwen Dai

PhD thesis, 2013

What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach.

Zhenwen Dai, Georgios Exarchakis, Jörg Lücke

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Autonomous cleaning of corrupted scanned documents - A generative modeling approach.

Zhenwen Dai, Jörg Lücke

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Unsupervised learning of translation invariant occlusive components.

Zhenwen Dai, Jörg Lücke

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Pose estimation from reflections for specular surface recovery.

Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen

Proceedings of the IEEE International Conference on Computer Vision, 2011

2010

Specular Surface Recovery from Reflections of a Planar Pattern Undergoing an Unknown Pure Translation.

Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen

Proceedings of the Computer Vision - ACCV 2010, 2010

2009

Polygonal Light Source Estimation.

Dirk Schnieders, Kwan-Yee Kenneth Wong, Zhenwen Dai

Proceedings of the Computer Vision, 2009

2007

Understanding Research Field Evolving and Trend with Dynamic Bayesian Networks.

Jinlong Wang, Congfu Xu, Gang Li, Zhenwen Dai, Guojing Luo

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2007