Cover Image

Bayesian Circular Regression with von Mises Quasi-Processes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cohen, Yarden, Navarro, Alexandre Khae Wu, Frellsen, Jes, Turner, Richard E., Riemer, Raziel, Pakman, Ari
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Super-Efficient Exact Hamiltonian Monte Carlo for the von Mises Distribution
by: Pakman, Ari
Published: (2023)

Noise-Response Calibration: A Causal Intervention Protocol for LLM-Judges
by: Khomiakov, Maxim, et al.
Published: (2026)

An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms
by: Grünefeld, Nils, et al.
Published: (2026)

Navigating Uncertainty in Medical Image Segmentation
by: Zepf, Kilian, et al.
Published: (2024)

Consistent Amortized Clustering via Generative Flow Networks
by: Chelly, Irit, et al.
Published: (2025)

Learning Energy-Based Models by Self-normalising the Likelihood
by: Senetaire, Hugo, et al.
Published: (2025)

Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters
by: Arts, Marloes, et al.
Published: (2023)

Fast Sampling for Flows and Diffusions with Lazy and Point Mass Stochastic Interpolants
by: Damsholt, Gabriel, et al.
Published: (2026)

Latent Diffusion for Missing Data
by: Estad, Alberte Heering, et al.
Published: (2026)

Order-Agnostic Autoregressive Modelling with Missing Data
by: Peis, Ignacio, et al.
Published: (2026)

A Continuous Relaxation for Discrete Bayesian Optimization
by: Michael, Richard, et al.
Published: (2024)

MolMiner: Towards Controllable, 3D-Aware, Fragment-Based Molecular Design
by: Ortega-Ochoa, Raul, et al.
Published: (2024)

Hyper-Transforming Latent Diffusion Models
by: Peis, Ignacio, et al.
Published: (2025)

Exploring bidirectional bounds for minimax-training of Energy-based models
by: Geng, Cong, et al.
Published: (2025)

Supervised Guidance Training for Infinite-Dimensional Diffusion Models
by: Baker, Elizabeth L., et al.
Published: (2026)

Explainability as statistical inference
by: Senetaire, Hugo Henri Joseph, et al.
Published: (2022)

Scalable physical source-to-field inference with hypernetworks
by: James, Berian, et al.
Published: (2024)

A solution for the mean parametrization of the von Mises-Fisher distribution
by: Nonnenmacher, Marcel, et al.
Published: (2024)

Tracing Uncertainty in Language Model "Reasoning"
by: Grünefeld, Nils, et al.
Published: (2026)

Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification
by: Zepf, Kilian, et al.
Published: (2023)

Variance reduction of diffusion model's gradients with Taylor approximation-based control variate
by: Jeha, Paul, et al.
Published: (2024)

DINO as a von Mises-Fisher mixture model
by: Govindarajan, Hariprasath, et al.
Published: (2024)

Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo
by: Lee, Cheuk Kit, et al.
Published: (2025)

Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings
by: Jeha, Paul, et al.
Published: (2026)

Amortized Probabilistic Detection of Communities in Graphs
by: Wang, Yueqi, et al.
Published: (2020)

Kinetic Langevin Diffusion for Crystalline Materials Generation
by: Cornet, François, et al.
Published: (2025)

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health
by: Collett, Peter, et al.
Published: (2026)

LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language
by: Requeima, James, et al.
Published: (2024)

Safe Exploration Using Bayesian World Models and Log-Barrier Optimization
by: As, Yarden, et al.
Published: (2024)

Variational Inference for Bayesian MIDAS Regression
by: Simeone, Luigi
Published: (2026)

Bernstein-von Mises for Adaptively Collected Data
by: Du, Kevin, et al.
Published: (2025)

BARMPy: Bayesian Additive Regression Models Python Package
by: Van Boxel, Danielle
Published: (2024)

Bayesian Multiple Multivariate Density-Density Regression
by: Nguyen, Khai, et al.
Published: (2026)

MLoRQ: Bridging Low-Rank and Quantization for Transformer Compression
by: Gordon, Ofir, et al.
Published: (2025)

Learning Representations on the Unit Sphere: Investigating Angular Gaussian and von Mises-Fisher Distributions for Online Continual Learning
by: Michel, Nicolas, et al.
Published: (2023)

Bayesian Multivariate Density-Density Regression
by: Nguyen, Khai, et al.
Published: (2025)

Sparse Techniques for Regression in Deep Gaussian Processes
by: Latz, Jonas, et al.
Published: (2025)

A Cramér-von Mises Approach to Incentivizing Truthful Data Sharing
by: Clinton, Alex, et al.
Published: (2025)

Approximate Cross-validated Mean Estimates for Bayesian Hierarchical Regression Models
by: Zhang, Amy X., et al.
Published: (2020)

Warm Starts Accelerate Conditional Diffusion
by: Scholz, Jonas, et al.
Published: (2025)