Awesome Papers

• **"Bayesian Learning for Neural Networks."**
• **"Detecting and Characterizing Events."**
• **"Approximate inference for constructing astronomical catalogs from images."** - 1926.
• Juliacon 2017 Talk
• **"Shannon-inspired Statistical Computing for The Nanoscale Era."** - 107.
• Stanford Seminar
• STI Conference Presentation
• **"The Decline of Computers As a General Purpose Technology: Why Deep Learning and the End of Moore’s Law are Fragmenting Computing."**
• **"Learning a Variational Network for Reconstruction of Accelerated MRI Data."** - 3071.
• **"On learning optimized reaction-diffusion processes for effective image restoration."**
• **"The Accelerator Wall: Limits of Chip Specialization."** - Performance Computer Architecture* (HPCA'19).
• **"Deep Image Prior."**
• **"A Bayesian Perspective on the Deep Image Prior"**
• **"Transformations of high-level synthesis codes for high-performance computing."** - 1029.
• **"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?."**
• **"Distributed optimization and statistical learning via the alternating direction method of multipliers."** - 122.
• Microsoft Research Talk
• **"Uncertainty in Neural Networks: Bayesian Ensembling."**
• Interactive demo
• **"Stein Variational Gradient Descent Without Gradient."** - 1908
• **"Stein Variational Adaptive Importance Sampling."**
• **"Stein Point Markov Chain Monte Carlo"** - 1021
• **"Dynamical, Symplectic and Stochastic Perspectives on Gradient-Based Optimization."**
• ICM 2018 Talk
• **"Allocating Independent Subtasks on Parallel Processors."** - 1016, 1985.
• Ph.D. Thesis
• **"Bayesian Optimization for a Better Dessert."**
• **"Bayesian Optimization Meets Bayesian Optimal Stopping"** - 1506
• **"Projective Preferential Bayesian Optimization"**
• **"Task Bench: A Parameterized Benchmark for Evaluating Parallel Runtime Performance."**
• **"The Thermodynamic Variational Objective."**
• **"All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference."** - 1122, 2020.
• **"Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective."**
• **"Modified Hamiltonian Monte Carlo for Bayesian inference."**
• **"Image enhancement and denoising by complex diffusion processes."** - 1036.
• **"Anisotropic Gaussian Mutations for Metropolis Light Transport through Hessian-Hamiltonian Dynamics."**
• **"A Bayesian interactive optimization approach to procedural animation design."** - 112.
• **"An adaptive sequential Monte Carlo sampler."** - 438.
• "**Robust, Accurate Stochastic Optimization for Variational Inference.**"
• **"Parallel Tempering With a Variational Reference."** - 577.
• **"Random reshuffling: Simple analysis with vast improvements."** - 17320.
• **"Unbiased Markov chain Monte Carlo methods with couplings."**
• **"Diffusion Schrödinger bridge with applications to score-based generative modeling."** - 17709.
• **"Covariances, robustness and variational bayes."**
• **"Score-based diffusion meets annealed importance sampling."** - 21494.
• **"Controlled sequential Monte Carlo."**
• **"The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization."** - 6878.
• **"Schrodinger Bridge Samplers."**
• **"On Markov chain Monte Carlo methods for tall data."**
• Juliacon 2017 Talk
• STI Conference Presentation