summary statistics
Generating Origin-Destination Matrices in Neural Spatial Interaction Models
Agent-based models (ABMs) are proliferating as decision-making tools across policy areas in transportation, economics, and epidemiology.
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Multi-Task Learning from Summary Statistics: Supplementary Materials A Proofs A.1 Preliminaries
The proofs of Lemmas A.2 and A.3 follow from covering arguments and Bernstein's inequality; refer
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Predictive Approximate Bayesian Computation via Saddle Points
Yingxiang Yang, Bo Dai, Negar Kiyavash, Niao He
Neural Information Processing Systems http://nips.cc/
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A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Jeffrey Chan, Valerio Perrone, Jeffrey Spence, Paul Jenkins, Sara Mathieson, Yun Song
Neural Information Processing Systems http://nips.cc/
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- Health & Medicine > Therapeutic Area > Oncology (0.46)
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- Health & Medicine > Therapeutic Area > Oncology (0.46)
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Training neural operators to preserve invariant measures of chaotic attractors
In this setting, neural operators trained to minimize squared error losses, while capable of accurate short-term forecasts, often fail to reproduce statistical or structural properties of the dynamics over longer time horizons and can yield degenerate results.
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Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse
Cornelius Schröder, Ben James, Leon Lagnado, Philipp Berens
Neural Information Processing Systems http://nips.cc/
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