2 citations · 2 across the 2 of their papers we have counts for
10 papers
Dynamic Execution Horizon Prediction for Chunk-based Robot Policies
Yuchi Zhao, Miroslav Bogdanovic, Arjun Sohal +5
Action chunking has become a standard design in modern robot policies, from diffusion/flow policies to vision-language-action models, where the policy predicts a sequence of action…
Bayesian Optimization for General Reaction Conditions
Stefan P. Schmid, Ella Miray Rajaonson, Cher Tian Ser +6
General chemical reaction conditions that achieve consistently high performance across multiple substrates are important for practical applications such as library synthesis and hi…
Discrete Feynman-Kac Correctors
Mohsin Hasan, Viktor Ohanesian, Artem Gazizov +5
Discrete diffusion models have recently emerged as a promising alternative to the autoregressive approach for generating discrete sequences. Sample generation via gradual denoising…
Informing Acquisition Functions via Foundation Models for Molecular Discovery
Qi Chen, Fabio Ramos, Alán Aspuru-Guzik +1
Bayesian Optimization (BO) is a key methodology for accelerating molecular discovery by estimating the mapping from molecules to their properties while seeking the optimal candidat…
AnyPlace: Learning Generalized Object Placement for Robot Manipulation
Yuchi Zhao, Miroslav Bogdanovic, Chengyuan Luo +5
Object placement in robotic tasks is inherently challenging due to the diversity of object geometries and placement configurations. To address this, we propose AnyPlace, a two-stag…
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian +6
While score-based generative models are the model of choice across diverse domains, there are limited tools available for controlling inference-time behavior in a principled manner…