Improving black-box optimization in VAE latent space using decoder uncertainty

30 June 2021

José Miguel Hernández-Lobato

Papers citing "Improving black-box optimization in VAE latent space using decoder uncertainty"

43 / 43 papers shown

Title
Latent Bayesian Optimization via Autoregressive Normalizing Flows Seunghun Lee Jinyoung Park Jaewon Chu Minseo Yoon H. Kim BDL 32 1 0 21 Apr 2025
Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems Yunyue Wei Zeji Yi Hongda Li Saraswati Soedarmadji Yanan Sui 31 0 0 31 Dec 2024
High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces Quoc-Anh Hoang Nguyen The Hung Tran 88 1 0 21 Dec 2024
Diffusion Model Guided Sampling with Pixel-Wise Aleatoric Uncertainty Estimation Michele De Vita Vasileios Belagiannis DiffM 93 1 0 29 Nov 2024
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences Miguel González Duque Richard Michael Simon Bartels Yevgen Zainchkovskyy Søren Hauberg Wouter Boomsma 44 4 0 07 Jun 2024
Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders Naﬁz Abeer Sanket R. Jantre Nathan M. Urban Byung-Jun Yoon 45 0 0 31 May 2024
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models Masatoshi Uehara Yulai Zhao Ehsan Hajiramezanali Gabriele Scalia Gökçen Eraslan Avantika Lal Sergey Levine Tommaso Biancalani 53 13 0 30 May 2024
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient Natavsa Tagasovska Vladimir Gligorijević Kyunghyun Cho Andreas Loukas DiffM 52 4 0 28 May 2024
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design A. N. M. N. Abeer Sanket R. Jantre Nathan M. Urban Byung-Jun Yoon 49 1 0 30 Apr 2024
A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators M. Rautela Alan Williams A. Scheinker 52 4 0 19 Mar 2024
Gradient-free neural topology optimization Gaweł Kuś Miguel A. Bessa AI4CE 35 0 0 07 Mar 2024
Feedback Efficient Online Fine-Tuning of Diffusion Models Masatoshi Uehara Yulai Zhao Kevin Black Ehsan Hajiramezanali Gabriele Scalia N. Diamant Alex Tseng Sergey Levine Tommaso Biancalani 36 21 0 26 Feb 2024
DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design Clare Lyle Arash Mehrjou Pascal Notin Andrew Jesson Stefan Bauer Y. Gal Patrick Schwab 49 10 0 07 Dec 2023
Joint Composite Latent Space Bayesian Optimization Natalie Maus Zhiyuan Jerry Lin Maximilian Balandat E. Bakshy BDL 33 2 0 03 Nov 2023
Advancing Bayesian Optimization via Learning Correlated Latent Space Seunghun Lee Jaewon Chu S. Kim Juyeon Ko Hyunwoo J. Kim BDL 46 6 0 31 Oct 2023
Prior Based Online Lane Graph Extraction from Single Onboard Camera Image Y. Can Alexander Liniger D. Paudel Luc Van Gool 26 2 0 25 Jul 2023
Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence Uncertainties Yassir Fathullah Guoxuan Xia Mark J. F. Gales UQCV 29 2 0 17 May 2023
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation Yiheng Zhu Zhenqiu Ouyang Ben Liao Jialun Wu YiXuan Wu Chang-Yu Hsieh Tingjun Hou Jian Wu AI4CE 24 5 0 15 May 2023
Who Needs Decoders? Efficient Estimation of Sequence-level Attributes Yassir Fathullah Puria Radmard Adian Liusie Mark J. F. Gales OODD 24 1 0 09 May 2023
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling Y. Yin Yu Wang Gang Xu 26 4 0 04 May 2023
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design Zaixin Zhang Qi Liu Cheekong Lee Chang-Yu Hsieh Enhong Chen 19 18 0 12 Apr 2023
Biological Sequence Kernels with Guaranteed Flexibility Alan N. Amin Eli N. Weinstein D. Marks 29 4 0 06 Apr 2023
Directional Connectivity-based Segmentation of Medical Images Ziyun Yang Sina Farsiu 30 36 0 31 Mar 2023
End-to-End Diffusion Latent Optimization Improves Classifier Guidance Bram Wallace Akash Gokul Stefano Ermon Nikhil Naik 124 70 0 23 Mar 2023
Automated patent extraction powers generative modeling in focused chemical spaces Akshay Subramanian Kevin P. Greenman Alexis Gervaix Tzuhsiung Yang Rafael Gómez-Bombarelli 38 6 0 14 Mar 2023
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings Aryan Deshwal Sebastian Ament Maximilian Balandat E. Bakshy J. Doppa David Eriksson 45 19 0 03 Mar 2023
GLSO: Grammar-guided Latent Space Optimization for Sample-efficient Robot Design Automation Jiaheng Hu Julian Whiman Howie Choset 36 14 0 23 Sep 2022
Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach Arpan Biswas Rama K Vasudevan M. Ziatdinov Sergei V. Kalinin BDL DRL 19 10 0 30 Jun 2022
LIMO: Latent Inceptionism for Targeted Molecule Generation Peter Eckmann Kunyang Sun Bo-Lu Zhao Mudong Feng Michael K. Gilson Rose Yu BDL 43 44 0 17 Jun 2022
High-Dimensional Bayesian Optimization with Constraints: Application to Powder Weighing Shoki Miyagawa Atsuyoshi Yano N. Sawada Isamu Ogawa 19 0 0 13 Jun 2022
Meta-Learning Parameterized Skills Haotian Fu Shangqun Yu Saket Tiwari Michael Littman George Konidaris 35 6 0 07 Jun 2022
PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations Tong Sang Hongyao Tang Yi Ma Jianye Hao Yan Zheng Zhaopeng Meng Boyan Li Zhen Wang OffRL 22 5 0 06 Apr 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 31 86 0 28 Mar 2022
Multi-Objective Latent Space Optimization of Generative Molecular Design Models Naﬁz Abeer Nathan M. Urban Ryan Weil Francis J. Alexander Byung-Jun Yoon 23 15 0 01 Mar 2022
Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spaces Jaeyeon Ahn Taehyeon Kim Seyoung Yun 24 0 0 02 Feb 2022
Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus Haydn Thomas Jones Juston Moore Matt J. Kusner John Bradshaw Jacob R. Gardner BDL 51 69 0 28 Jan 2022
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces Aryan Deshwal J. Doppa BDL 32 42 0 01 Nov 2021
Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection Yi Shen Carl Kingsford 44 8 0 20 Sep 2021
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation Boyan Li Hongyao Tang Yan Zheng Jianye Hao Pengyi Li Zhen Wang Zhaopeng Meng Li Wang 29 42 0 12 Sep 2021
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning Antoine Grosnit Rasul Tutunov A. Maraval Ryan-Rhys Griffiths Alexander I. Cowen-Rivers ... Wenlong Lyu Zhitang Chen Jun Wang Jan Peters Haitham Bou-Ammar BDL DRL 22 59 0 07 Jun 2021
What About Inputing Policy in Value Function: Policy Representation and Policy-extended Value Function Approximator Hongyao Tang Zhaopeng Meng Jianye Hao Cheng Chen D. Graves ... Hangyu Mao Wulong Liu Yaodong Yang Wenyuan Tao Li Wang OffRL 8 7 0 19 Oct 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,340 0 12 Feb 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015