Zhenwen Dai

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 40

Top Venues

Goethe University Frankfurt am Main (PHD)

Education History

Goethe University Frankfurt am Main

PHD

Publications

Zhenwen Dai, Federico Tomasi, Sina Ghiassian
In-context Exploration-Exploitation for Reinforcement Learning. CoRR (2024)
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
In-context Exploration-Exploitation for Reinforcement Learning. ICLR (2024)
Matthew Smith, Lucas Maystre, Zhenwen Dai, Kamil Ciosek
A Strong Baseline for Batch Imitation Learning. CoRR (2023)
Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics. CoRR (2023)
Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics. J. Mach. Learn. Res. 24 (2023)
Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. KDD (2023)
Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. CoRR (2023)
Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke
The ELBO of Variational Autoencoders Converges to a Sum of Entropies. AISTATS (2023)
Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas
Exploiting Sequential Music Preferences via Optimisation-Based Sequencing. CIKM (2023)
Federico Tomasi, Mounia Lalmas, Zhenwen Dai
Efficient inference for dynamic topic modeling with large vocabularies. UAI (2022)
Erik Bodin, Federico Tomasi, Zhenwen Dai
Making Differentiable Architecture Search less local. CoRR (2021)
Erik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
Black-box density function estimation using recursive partitioning. ICML (2021)
Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Ben Carterette, Mounia Lalmas-Roelleke
Model Selection for Production System via Automated Online Experiments. CoRR (2021)
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
Modulating Surrogates for Bayesian Optimization. ICML (2020)
Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan
Data-Driven Mode Identification and Unsupervised Fault Detection for Nonlinear Multimode Processes. IEEE Trans. Ind. Informatics 16 (6) (2020)
Jörg Lücke, Dennis Forster, Zhenwen Dai
The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies. CoRR (2020)
Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek
Black-box density function estimation using recursive partitioning. CoRR (2020)
Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Benjamin A. Carterette, Mounia Lalmas
Model Selection for Production System via Automated Online Experiments. NeurIPS (2020)
Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai
Stochastic Variational Inference for Dynamic Correlated Topic Models. UAI (2020)
Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke
ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. CoRR (2019)
Abdul-Saboor Sheikh, Nicol S. Harper, Jakob Drefs, Yosef Singer, Zhenwen Dai, Richard E. Turner, Jörg Lücke
STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds. PLoS Comput. Biol. 15 (1) (2019)
Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier Gonzalez
Meta-Surrogate Benchmarking for Hyperparameter Optimization. NeurIPS (2019)
Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai
Variational Information Distillation for Knowledge Transfer. CVPR (2019)
Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai
Variational Information Distillation for Knowledge Transfer. CoRR (2019)
Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier Gonzalez
Meta-Surrogate Benchmarking for Hyperparameter Optimization. CoRR (2019)
Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan
A probabilistic principal component analysis-based approach in process monitoring and fault diagnosis with application in wastewater treatment plant. Appl. Soft Comput. 82 (2019)
Jörg Lücke, Zhenwen Dai, Georgios Exarchakis
Truncated Variational Sampling for 'Black Box' Optimization of Generative Models. LVA/ICA (2018)
Mu Niu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil D. Lawrence, David B. Dunson
Intrinsic Gaussian processes on complex constrained domains. CoRR (2018)
Xiaoyu Lu, Javier Gonzalez, Zhenwen Dai, Neil D. Lawrence
Structured Variationally Auto-encoded Optimization. ICML (2018)
Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. CoRR (2017)
Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton
GP-Select: Accelerating EM Using Adaptive Subspace Preselection. Neural Comput. 29 (8) (2017)
Javier González, Zhenwen Dai, Andreas C. Damianou, Neil D. Lawrence
Preferential Bayesian Optimization. ICML (2017)
Zhenwen Dai, Mudassar Iqbal, Neil D. Lawrence, Magnus Rattray
Efficient inference for sparse latent variable models of transcriptional regulation. Bioinform. 33 (23) (2017)
Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. NIPS (2017)
Matthias W. Seeger, Asmus Hetzel, Zhenwen Dai, Neil D. Lawrence
Auto-Differentiating Linear Algebra. CoRR (2017)
Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek, Neil D. Lawrence
Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model. CoRR (2016)
José A. Rodríguez-Serrano, Diane Larlus, Zhenwen Dai
Data-Driven Detection of Prominent Objects. IEEE Trans. Pattern Anal. Mach. Intell. 38 (10) (2016)
César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence
Recurrent Gaussian Processes. ICLR (Poster) (2016)
Javier González, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence
Batch Bayesian Optimization via Local Penalization. AISTATS (2016)
Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence
Variational Auto-encoded Deep Gaussian Processes. ICLR (Poster) (2016)
Zhenwen Dai, James Hensman, Neil D. Lawrence
Spike and Slab Gaussian Process Latent Variable Models. CoRR (2015)
Zhenwen Dai, Andreas C. Damianou, James Hensman, Neil D. Lawrence
Gaussian Process Models with Parallelization and GPU acceleration. CoRR (2014)
Zhenwen Dai, Jörg Lücke
Autonomous Document Cleaning - A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts. IEEE Trans. Pattern Anal. Mach. Intell. 36 (10) (2014)
Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton
GP-select: Accelerating EM using adaptive subspace preselection. CoRR (2014)
Zhenwen Dai, Georgios Exarchakis, Jörg Lücke
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach. NIPS (2013)
Zhenwen Dai, Jörg Lücke
Autonomous cleaning of corrupted scanned documents - A generative modeling approach. CVPR (2012)
Zhenwen Dai, Jörg Lücke
Autonomous Cleaning of Corrupted Scanned Documents - A Generative Modeling Approach CoRR (2012)
Zhenwen Dai, Jörg Lücke
Unsupervised learning of translation invariant occlusive components. CVPR (2012)
Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen
Pose estimation from reflections for specular surface recovery. ICCV (2011)
Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen
Specular Surface Recovery from Reflections of a Planar Pattern Undergoing an Unknown Pure Translation. ACCV (2) (2010)
Dirk Schnieders, Kwan-Yee Kenneth Wong, Zhenwen Dai
Polygonal Light Source Estimation. ACCV (3) (2009)
Jinlong Wang, Congfu Xu, Gang Li, Zhenwen Dai, Guojing Luo
Understanding Research Field Evolving and Trend with Dynamic Bayesian Networks. PAKDD (2007)

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Publication Activity (10 Years)

Top Topics

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Zhenwen Dai