gemlib.mcmc supplies composable kernel abstractions for Metropolis-within-Gibbs sampling via writer monads, allowing concise expression and reuse of complex MCMC algorithms for partially observed epidemic models.
PLOS Com- putational Biology18(9)
5 Pith papers cite this work. Polarity classification is still indexing.
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A recurrent SNN with heterogeneous synaptic delays (D=41) achieves perfect F1=1.0 recall of 16 arbitrary spike patterns on a synthetic benchmark by representing them as chains of overlapping spiking motifs.
VeloTree infers differentiation trees from RNA velocity fields by defining cell dissimilarity as the squared varifold distance between integral curves of the velocity field.
Optimal LPC networks achieve near-minimal response times without trade-offs in energetic cost or robustness, and modular structures with reduced lateral connections match all-to-all networks in performance.
A practical guide that organizes seven IT measures around three questions each—what it answers in AI, suitable estimators, and dangerous misuses—complete with flowchart, table, and worked examples.
citing papers explorer
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gemlib.mcmc: composable kernels for Metropolis-within-Gibbs sampling schemes
gemlib.mcmc supplies composable kernel abstractions for Metropolis-within-Gibbs sampling via writer monads, allowing concise expression and reuse of complex MCMC algorithms for partially observed epidemic models.
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Working Memory in a Recurrent Spiking Neural Networks With Heterogeneous Synaptic Delays
A recurrent SNN with heterogeneous synaptic delays (D=41) achieves perfect F1=1.0 recall of 16 arbitrary spike patterns on a synthetic benchmark by representing them as chains of overlapping spiking motifs.
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VeloTree: Inferring single-cell trajectories from RNA velocity fields with varifold distances
VeloTree infers differentiation trees from RNA velocity fields by defining cell dissimilarity as the squared varifold distance between integral curves of the velocity field.
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Response time of lateral predictive coding and benefits of modular structures
Optimal LPC networks achieve near-minimal response times without trade-offs in energetic cost or robustness, and modular structures with reduced lateral connections match all-to-all networks in performance.
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Information-Theoretic Measures in AI: A Practical Decision Guide
A practical guide that organizes seven IT measures around three questions each—what it answers in AI, suitable estimators, and dangerous misuses—complete with flowchart, table, and worked examples.