Jonathan Ho
18 papers · 2013–2023 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (25) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Keyword Trendsetter Combo
(5)
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Deep Specialist
(11)
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Topic Evolution
π§
Keyword Pioneer
π
Trend Setter
ποΈ
Keyword Collector
(86)
β‘
Prolific Year Β· Productive
π₯
Unstoppable Β· Bronze
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Century Club Β· Bronze
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Conference Pioneer
Top co-authors
Research topics
Deep Learning
(14)
Models
(14)
Computer Vision
(8)
Generation
(8)
Machine Learning
(7)
Artificial Intelligence
(4)
Learning Types Β· Machine Learning
(4)
Reinforcement Learning
(3)
Learning Paradigms
(3)
Optimization & Theory
(3)
Core AI
(2)
Learning Types Β· Deep Learning
(2)
Methods
(2)
Mathematics & Optimization
(1)
Analysis
(1)
Keywords
diffusion model
(11)
image generation
(7)
generative model
(4)
image synthesis
(3)
variational inference
(3)
imitation learning
(2)
likelihood-based model
(2)
policy learning
(2)
variational lower bound
(2)
latent space
(2)
latent variable model
(2)
knowledge distillation
(2)
lossless compression
(2)
bits-back coding
(2)
video prediction
(1)
video generation
(1)
hierarchical learning
(1)
policy gradient
(1)
reinforcement learning
(1)
motion planning
(1)
Papers
Discrete Predictor-Corrector Diffusion Models for Image Synthesis
ICLR 2023
Novel View Synthesis with Diffusion Models
ICLR 2023
On Distillation of Guided Diffusion Models
CVPR 2023
Cascaded Diffusion Models for High Fidelity Image Generation
JMLR 2022
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
ICLR 2022
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
NeurIPS 2022
Progressive Distillation for Fast Sampling of Diffusion Models
ICLR 2022
Video Diffusion Models
NeurIPS 2022
Structured Denoising Diffusion Models in Discrete State-Spaces
NeurIPS 2021
Variational Diffusion Models
NeurIPS 2021
Denoising Diffusion Probabilistic Models
NeurIPS 2020
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
ICML 2019
Compression with Flows via Local Bits-Back Coding
NeurIPS 2019
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
ICML 2019
META LEARNING SHARED HIERARCHIES
ICLR 2018
Generative Adversarial Imitation Learning
NeurIPS 2016
Model-Free Imitation Learning with Policy Optimization
ICML 2016
Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization
RSS 2013