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Sam McCallum

3 papers

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papers

Publications (3)

cs.LG2026

Strong Stochastic Flow Maps

Sam McCallum, Zander W. Blasingame, Timothy Herschell +3

Flow and diffusion models generate high-quality samples in many modalities; however, many network evaluations are required during inference due to numerical integration of an under…

cs.LG2025

Efficient, Accurate and Stable Gradients for Neural ODEs

Sam McCallum, James Foster

Training Neural ODEs requires backpropagating through an ODE solve. The state-of-the-art backpropagation method is recursive checkpointing that balances recomputation with memory c…

cs.LG2025

Reversible Deep Equilibrium Models

Sam McCallum, Kamran Arora, James Foster

Deep Equilibrium Models (DEQs) are an interesting class of implicit model where the model output is implicitly defined as the fixed point of a learned function. These models have b…

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