More from the Same Authors

• 2020 : Scalable Combinatorial Bayesian Optimization with Tractable Statistical models »
  Aryan Deshwal · Syrine Belakaria · Janardhan Rao Doppa
• 2020 : Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations »
  Syrine Belakaria · Aryan Deshwal · Janardhan Rao Doppa
• 2022 : Efficient Variational Gaussian Processes Initialization via Kernel-based Least Squares Fitting »
  Xinran Zhu · David Bindel · Jacob Gardner
• 2022 : Preference-Aware Constrained Multi-Objective Bayesian Optimization »
  Alaleh Ahmadian · Syrine Belakaria · Janardhan Rao Doppa
• 2022 : Preference-Aware Constrained Multi-Objective Bayesian Optimization »
  Alaleh Ahmadian · Syrine Belakaria · Janardhan Rao Doppa
• 2023 Poster: Variational Gaussian Processes with Decoupled Conditionals »
  Xinran Zhu · Kaiwen Wu · Natalie Maus · Jacob Gardner · David Bindel
• 2023 Poster: Black-Box Variational Inference Converges »
  Kyurae Kim · Kaiwen Wu · Jisu Oh · Yian Ma · Jacob Gardner
• 2023 Poster: The Behavior and Convergence of Local Bayesian Optimization »
  Kaiwen Wu · Kyurae Kim · Roman Garnett · Jacob Gardner
• 2022 Tutorial: Advances in Bayesian Optimization »
  Janardhan Rao Doppa · Virginia Aglietti · Jacob Gardner
• 2022 : Tutorial part 1 »
  Jacob Gardner · Virginia Aglietti · Janardhan Rao Doppa
• 2022 : Panel Discussion »
  Jacob Gardner · Marta Blangiardo · Viacheslav Borovitskiy · Jasper Snoek · Paula Moraga · Carolina Osorio
• 2022 Poster: Local Bayesian optimization via maximizing probability of descent »
  Quan Nguyen · Kaiwen Wu · Jacob Gardner · Roman Garnett
• 2022 Poster: Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients »
  Kyurae Kim · Jisu Oh · Jacob Gardner · Adji Bousso Dieng · Hongseok Kim
• 2022 Poster: Local Latent Space Bayesian Optimization over Structured Inputs »
  Natalie Maus · Haydn Jones · Juston Moore · Matt Kusner · John Bradshaw · Jacob Gardner
• 2021 Poster: Dynamic Causal Bayesian Optimization »
  Virginia Aglietti · Neil Dhir · Javier González · Theodoros Damoulas
• 2021 Poster: Scaling Gaussian Processes with Derivative Information Using Variational Inference »
  Misha Padidar · Xinran Zhu · Leo Huang · Jacob Gardner · David Bindel
• 2020 Poster: Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization »
  Geoff Pleiss · Martin Jankowiak · David Eriksson · Anil Damle · Jacob Gardner
• 2020 Poster: Multi-task Causal Learning with Gaussian Processes »
  Virginia Aglietti · Theodoros Damoulas · Mauricio Álvarez · Javier González
• 2020 Poster: Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees »
  Shali Jiang · Daniel Jiang · Maximilian Balandat · Brian Karrer · Jacob Gardner · Roman Garnett
• 2019 Poster: Max-value Entropy Search for Multi-Objective Bayesian Optimization »
  Syrine Belakaria · Aryan Deshwal · Janardhan Rao Doppa
• 2019 Poster: Structured Variational Inference in Continuous Cox Process Models »
  Virginia Aglietti · Edwin Bonilla · Theodoros Damoulas · Sally Cripps