Daniel Sheldon
26 papers · 2013–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (18) π Conference Polyglot (9)
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Conference Polyglot
(9)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Keyword Champion
(3)
ποΈ
Keyword Collector
(117)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(26)
π₯
Unstoppable
(13)
β‘
Prolific Year
(7)
Conferences
AISTATS (7)
ICML (6)
IJCAI (3)
NIPS (3)
AAAI (2)
ICCV (2)
CVPR (1)
ECCV (1)
UAI (1)
Top co-authors
Research topics
Keywords
differential privacy
(5)
bayesian inference
(4)
graphical model
(4)
collective graphical model
(3)
gaussian process
(3)
approximate inference
(2)
active learning
(2)
object detection
(2)
hamiltonian monte carlo
(2)
probabilistic programming
(2)
markov chain monte carlo
(2)
synthetic datum
(2)
em algorithm
(2)
parameter estimation
(1)
statistical inference
(1)
convex optimization
(1)
population estimation
(1)
image restoration
(1)
model selection
(1)
person re-identification
(1)
Papers
Consensus-Driven Active Model Selection
ICCV 2025
Gaussian Process Bandits for Top-k Recommendations
NIPS 2024
Efficient and Private Marginal Reconstruction with Local Non-Negativity
NIPS 2024
DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling
AAAI 2024
Sample Average Approximation for Black-Box Variational Inference
UAI 2024
Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
AISTATS 2024
Human-in-the-Loop Visual Re-ID for Population Size Estimation
ECCV 2024
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
NIPS 2024
Automatically marginalized MCMC in probabilistic programming
ICML 2023
Variational Marginal Particle Filters
AISTATS 2022
Parametric Bootstrap for Differentially Private Confidence Intervals
AISTATS 2022
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data
ICCV 2021
Faster Kernel Interpolation for Gaussian Processes
AISTATS 2021
Detecting and Tracking Communal Bird Roosts in Weather Radar Data
AAAI 2020
A Bayesian Perspective on the Deep Image Prior
CVPR 2019
Graphical-model based estimation and inference for differential privacy
ICML 2019
Three-quarter Sibling Regression for Denoising Observational Data
IJCAI 2019
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
ICML 2018
Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models
ICML 2017
Consistently Estimating Markov Chains with Noisy Aggregate Data
AISTATS 2016
Approximate Inference Using DC Programming For Collective Graphical Models
AISTATS 2016
Fast Combinatorial Algorithm for Optimizing the Spread of Cascades
IJCAI 2015
Dynamic Resource Allocation for Optimizing Population Diffusion
AISTATS 2014
Gaussian Approximation of Collective Graphical Models
ICML 2014
Approximate Inference in Collective Graphical Models
ICML 2013
Parameter Learning for Latent Network Diffusion
IJCAI 2013