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PaCMO: Partner Dependent Human Motion Generation in Dyadic Human Activity using Neural Operators
Md Ashiqur Rahman, Jasorsi Ghosh, Hrishikesh Viswanath +2
We address the problem of generating 3D human motions in dyadic activities. In contrast to the concurrent works, which mainly focus on generating the motion of a single actor from…
Fast Sampling of Diffusion Models via Operator Learning
Hongkai Zheng, Weili Nie, Arash Vahdat +2
Diffusion models have found widespread adoption in various areas. However, their sampling process is slow because it requires hundreds to thousands of network evaluations to emulat…
Accelerating Time-Reversal Imaging with Neural Operators for Real-time Earthquake Locations
Hongyu Sun, Yan Yang, Kamyar Azizzadenesheli +2
Earthquake hypocenters form the basis for a wide array of seismological analyses. Pick-based earthquake location workflows rely on the accuracy of phase pickers and may be biased w…
Real-time high-resolution CO geological storage prediction using nested Fourier neural operators
Gege Wen, Zongyi Li, Qirui Long +3
Carbon capture and storage (CCS) plays an essential role in global decarbonization. Scaling up CCS deployment requires accurate and high-resolution modeling of the storage reservoi…
Off-Policy Risk Assessment in Markov Decision Processes
Audrey Huang, Liu Leqi, Zachary Chase Lipton +1
Addressing such diverse ends as safety alignment with human preferences, and the efficiency of learning, a growing line of reinforcement learning research focuses on risk functiona…
Rapid Seismic Waveform Modeling and Inversion with Neural Operators
Yan Yang, Angela F. Gao, Kamyar Azizzadenesheli +2
Seismic waveform modeling is a powerful tool for determining earth structure models and unraveling earthquake rupture processes, but it is usually computationally expensive. We int…