Daniel R. Sheldon
13 papers · 2007–2022 · 1 venue · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+6 more ↓ Show less ↑
π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (30) π Academic Marathon Β· Full π Interdisciplinary Bridge Β· Silver π± Topic Pioneer
π
Keyword Champion
π
Trend Setter
π
Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(69)
Venues
Top co-authors
Research topics
Machine Learning
(12)
Optimization & Theory
(9)
Artificial Intelligence
(8)
Bayesian & Probabilistic Β· Artificial Intelligence
(8)
Bayesian & Probabilistic Β· Machine Learning
(7)
Mathematics & Optimization
(4)
Application Areas
(4)
Core Methods
(4)
Deep Learning
(3)
Core AI
(3)
Mathematics
(3)
Models
(3)
Data Science & Analytics
(2)
Methods
(2)
Optimization
(2)
Keywords
differential privacy
(4)
variational inference
(3)
probabilistic inference
(3)
bayesian inference
(2)
gaussian process
(2)
stochastic optimization
(2)
graphical model
(2)
bird migration
(2)
importance weighting
(2)
posterior distribution
(2)
latent variable model
(2)
importance sampling
(1)
monte carlo estimation
(1)
dynamic programming
(1)
statistical modeling
(1)
ecological modeling
(1)
markov chain monte carlo
(1)
viterbi algorithm
(1)
sample path reconstruction
(1)
gibbs sampling
(1)
Papers
Kernel Interpolation with Sparse Grids
NeurIPS 2022
Relaxed Marginal Consistency for Differentially Private Query Answering
NeurIPS 2021
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization
NeurIPS 2020
Permute-and-Flip: A new mechanism for differentially private selection
NeurIPS 2020
Differentially Private Bayesian Linear Regression
NeurIPS 2019
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
NeurIPS 2019
Differentially Private Bayesian Inference for Exponential Families
NeurIPS 2018
Importance Weighting and Variational Inference
NeurIPS 2018
Inferring Latent Velocities from Weather Radar Data using Gaussian Processes
NeurIPS 2018
Probabilistic Inference with Generating Functions for Poisson Latent Variable Models
NeurIPS 2016
Stochastic Network Design in Bidirected Trees
NeurIPS 2014
Collective Graphical Models
NeurIPS 2011
Collective Inference on Markov Models for Modeling Bird Migration
NeurIPS 2007