32 citations · 45 across the 7 of their papers we have counts for
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cs.LG2024
INRFlow: Flow Matching for INRs in Ambient Space
Yuyang Wang, Anurag Ranjan, Josh Susskind +1
Flow matching models have emerged as a powerful method for generative modeling on domains like images or videos, and even on irregular or unstructured data like 3D point clouds or…
cs.LG2021★ 2 cited
LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time
Elvis Nunez, Maxwell Horton, Anish Prabhu +3
When deploying deep learning models to a device, it is traditionally assumed that available computational resources (compute, memory, and power) remain static. However, real-world…