Rotational transits of WASP-121 b observed with JWST/NIRSpec and NIRISS show asymmetric light curves and phase-dependent molecular absorption revealing stronger evening than morning terminator temperature gradients.
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Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro
Mixed citation behavior. Most common role is background (60%).
84
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230
external citations · Pith
Background
60% of classified citations
abstract
NumPyro is a lightweight library that provides an alternate NumPy backend to the Pyro probabilistic programming language with the same modeling interface, language primitives and effect handling abstractions. Effect handlers allow Pyro's modeling API to be extended to NumPyro despite its being built atop a fundamentally different JAX-based functional backend. In this work, we demonstrate the power of composing Pyro's effect handlers with the program transformations that enable hardware acceleration, automatic differentiation, and vectorization in JAX. In particular, NumPyro provides an iterative formulation of the No-U-Turn Sampler (NUTS) that can be end-to-end JIT compiled, yielding an implementation that is much faster than existing alternatives in both the small and large dataset regimes.
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representative citing papers
NumPyro delivers a JIT-compilable iterative NUTS sampler by composing Pyro effect handlers with JAX transformations, achieving faster performance than prior implementations.
Splitting an attack across more coordinating agents lowers per-commit monitor suspicion, making distributed attacks harder to detect than single-agent attacks.
A standardizing coordinate transform turns PTA Fourier coefficients into near-standard normals so HMC/NUTS on GPU recovers NANOGrav-scale posteriors in ~15 minutes.
Hierarchical Bayesian power-law fits to early ZTF light curves of 972 SNe Ia yield population parameters for rise time, index, and color evolution, revealing a bifurcation with SALT2 stretch.
A hierarchical Bayesian approach with multivariate Gaussian population prior reduces bias in demographic inference of SN Ia power-law rise parameters compared to individual fitting.
Bayesian workflow diagnostics outperform unit tests for detecting and repairing statistically misspecified LLM-generated probabilistic programs across benchmarks and real generation tasks.
A new RTU grid method models the lensing source as a Gaussian process on a ray-transformed uniform grid, achieving comparable fits with roughly half the pixels per dimension and higher ELBOs on mock data.
A hierarchical Bayesian framework that uses the empirical anti-correlation between AGN variability amplitude and luminosity to infer cosmological parameters from moderate-baseline light curves via importance reweighting.
All 18 audited MLLMs exhibit order sensitivity with per-facet flip rates of 24-50%, exceeding same-order decoder noise.
Multidimensional IRT analysis of 34k FCI administrations identifies 22 robust misconception dimensions and computes student/class scores revealing varied post-instruction remediation patterns.
DREAM enables exact-gradient Bayesian calibration of nuclear models via offline SVD emulation of parameter-dependent operators, demonstrated by rapid HMC convergence on an 18-parameter CDCC analysis of d+58Ni scattering.
Equivalent Wishart Ansatz for kernel renormalization in Bayesian MLPs and CNNs in the proportional regime, with tests showing good agreement on benchmarks.
acopula enables polynomial-time exact inference for arbitrary nested Archimedean copulas with censoring via Taylor-mode AD on user-defined generators.
A new queryable binary dataset combining cross-build diversity, temporal history, and CVE labels with linked metadata for vulnerability research.
Derives Wasserstein bounds and explicit hyperparameter tuning rules for annealed Langevin dynamics in compositional score-based SBI, proving Linhart et al. (2026) allows larger steps and fewer total steps than Geffner et al. (2023) in the Gaussian case.
Bayesian nonparametric model for dynamic sparse networks with overlapping communities via completely random measures and latent Markov processes.
Large longitudinal RCT finds high rates of following AI personal advice but no sustained well-being gains versus a hobbies control condition.
AMIGO is an end-to-end differentiable forward model of JWST AMI that corrects detector systematics to recover high-precision astrometry and detect close high-contrast companions.
Using survey and experimental data, the paper reports that conversational AI is a common source of political information in the UK and that its effect on belief in true versus false statements statistically does not exceed internet search, although the equivalence claim is fragile.
Symbolic regression yields an emulator for the radial Fourier transform of the Sérsic profile that enables 2.5 times faster galaxy profile fitting with minimal accuracy loss.
Introduces HICOBIAN, a differentiable fuzzy hierarchical cosmic-web bias model using sigmoid gradients for smooth region transitions, enabling accurate Bayesian field-level reconstruction of primordial density fields validated by Fourier-space statistics.
Extends NPE to mixed discrete-continuous parameter spaces via a factorized inference network combining an autoregressive classifier and generative model, trained jointly to yield accurate calibrated posteriors.
Variational predictive resampling iteratively imputes data from a variational predictive to produce posterior samples that converge to the exact Bayesian posterior in Gaussian models where mean-field VI retains a gap.
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