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John Paisley

Identifiers

  • name variant John Paisley 0.60 · backfill

Papers (48)

  1. Calibration, Not Compilation: Detecting and Repairing Misspecified Probabilistic Programs Written by Language Models cs.LG · 2026 · author #3
  2. What Do Flow-Based Inverse Solvers Approximate? A Posterior-Transport View cs.CV · 2026 · author #3
  3. Intrinsic Flow Matching on Quantum Pure-State Manifolds with Phase-Aligned Transport cs.LG · 2026 · author #3
  4. Effective Dimension Governs Generalization in Quantum Kernel Vision Models cs.LG · 2026 · author #3
  5. Higher-Order Token Interactions via Quantum Attention quant-ph · 2026 · author #4
  6. The Right Measure for Physics-Constrained Generation: A Co-Area Correction for Posterior-Consistent PDE Inverse Problems cs.LG · 2026 · author #4
  7. Spectral Anatomy of Quantum Gaussian Process Kernels cs.LG · 2026 · author #6
  8. Onsager-Machlup Posterior Transport for Deep Gaussian Processes cs.LG · 2026 · author #3
  9. AQKA: Active Quantum Kernel Acquisition Under a Shot Budget cs.LG · 2026 · author #4
  10. Stochastic Schr\"odinger Diffusion Models for Pure-State Ensemble Generation stat.ML · 2026 · author #5
  11. Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner cs.LG · 2026 · author #6
  12. One-Step Score-Based Density Ratio Estimation stat.ML · 2026 · author #3
  13. A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimation cs.LG · 2026 · author #6
  14. Consist-Retinex: One-Step Noise-Emphasized Consistency Training Accelerates High-Quality Retinex Enhancement cs.CV · 2025 · author #5
  15. Neural Bridge Processes cs.LG · 2025 · author #4
  16. Random Function Priors for Correlation Modeling cs.LG · 2019 · author #2
  17. Adaptive Ensemble Learning of Spatiotemporal Processes with Calibrated Predictive Uncertainty: A Bayesian Nonparametric Approach stat.ME · 2019 · author #2
  18. Global Explanations of Neural Networks: Mapping the Landscape of Predictions cs.LG · 2019 · author #4
  19. Mixed Membership Recurrent Neural Networks cs.LG · 2018 · author #5
  20. Adaptive and Calibrated Ensemble Learning with Dependent Tail-free Process cs.LG · 2018 · author #2
  21. A Deep Tree-Structured Fusion Model for Single Image Deraining cs.CV · 2018 · author #6
  22. Towards Explainable Deep Learning for Credit Lending: A Case Study cs.LG · 2018 · author #4
  23. An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection cs.CV · 2018 · author #6
  24. Fully Supervised Speaker Diarization eess.AS · 2018 · author #4
  25. MBA: Mini-Batch AUC Optimization cs.LG · 2018 · author #4
  26. Lightweight Pyramid Networks for Image Deraining cs.CV · 2018 · author #5
  27. Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network cs.CV · 2018 · author #5
  28. A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI cs.CV · 2018 · author #6
  29. A Divide-and-Conquer Approach to Compressed Sensing MRI cs.CV · 2018 · author #6
  30. A Deep Error Correction Network for Compressed Sensing MRI cs.CV · 2018 · author #5
  31. Online Forecasting Matrix Factorization cs.LG · 2017 · author #2
  32. Location Dependent Dirichlet Processes stat.ML · 2017 · author #2
  33. Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network cs.CV · 2017 · author #6
  34. Nonlinear Kalman Filtering with Divergence Minimization math.OC · 2017 · author #2
  35. TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency cs.CL · 2016 · author #4
  36. Variational Inference via $\chi$-Upper Bound Minimization stat.ML · 2016 · author #4
  37. Clearing the Skies: A deep network architecture for single-image rain removal cs.CV · 2016 · author #5
  38. A constructive definition of the beta process math.ST · 2016 · author #1
  39. Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts stat.ML · 2015 · author #2
  40. Stochastic Annealing for Variational Inference stat.ML · 2015 · author #3
  41. A Collaborative Kalman Filter for Time-Evolving Dyadic Processes stat.ML · 2015 · author #2
  42. Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI cs.CV · 2013 · author #2
  43. A Nested HDP for Hierarchical Topic Models stat.ML · 2013 · author #1
  44. Nested Hierarchical Dirichlet Processes stat.ML · 2012 · author #1
  45. Stochastic Variational Inference stat.ML · 2012 · author #4
  46. Combinatorial clustering and the beta negative binomial process stat.ME · 2011 · author #3
  47. The Stick-Breaking Construction of the Beta Process as a Poisson Process math.ST · 2011 · author #1
  48. The Discrete Infinite Logistic Normal Distribution stat.ML · 2011 · author #1

Mentions

  • 2606.31630 #3 · arxiv_oai · confidence 0.70 John Paisley
  • 2606.24516 #3 · arxiv_oai · confidence 0.70 John Paisley
  • 2606.21256 #3 · arxiv_oai · confidence 0.70 John Paisley
  • 2606.20183 #3 · arxiv_oai · confidence 0.70 John Paisley
  • 2606.11673 #4 · arxiv_oai · confidence 0.70 John Paisley
  • 2606.04804 #4 · arxiv_oai · confidence 0.70 John Paisley
  • 1506.03493 #2 · backfill · confidence 0.70 John Paisley
  • 1505.06723 #3 · backfill · confidence 0.70 John Paisley
  • 1501.05624 #2 · backfill · confidence 0.70 John Paisley
  • 2605.30952 #6 · arxiv_oai · confidence 0.70 John Paisley
  • 1302.2712 #2 · backfill · confidence 0.70 John Paisley
  • 1301.3570 #1 · backfill · confidence 0.70 John Paisley
  • 2605.23434 #3 · arxiv_oai · confidence 0.70 John Paisley
  • 1210.6738 #1 · backfill · confidence 0.70 John Paisley
  • 1206.7051 #4 · backfill · confidence 0.70 John Paisley
  • 1111.1802 #3 · backfill · confidence 0.70 John Paisley
  • 1109.0343 #1 · backfill · confidence 0.70 John Paisley
  • 1103.4789 #1 · backfill · confidence 0.70 John Paisley

Frequent Coauthors