Kyle Hsu
11 papers · 2019–2025 · 7 venues · 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 ↓+4 more ↓ Show less ↑
🗺️ Taxonomy Completionist (27) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🧬 Topic Evolution
👥
Mega-Team · Legion
🗃️
Keyword Collector
(54)
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(9)
Deep Learning
(6)
Core Methods
(4)
Robotics
(3)
Architectures
(3)
Capabilities
(3)
Learning Types · Deep Learning
(3)
Models
(3)
Optimization & Theory
(3)
Artificial Intelligence
(2)
Computer Vision
(2)
Reinforcement Learning
(2)
Application Areas
(2)
Core AI
(2)
Learning Types · Machine Learning
(2)
Keywords
representation learning
(4)
reinforcement learning
(2)
disentangled representation
(2)
unsupervised learning
(2)
policy evaluation
(1)
few-shot learning
(1)
stochastic gradient
(1)
prior distribution
(1)
density estimation
(1)
curriculum learning
(1)
visual navigation
(1)
out-of-distribution generalization
(1)
energy efficiency
(1)
marginal likelihood
(1)
differentiable programming
(1)
kullback-leibler divergence
(1)
posterior distribution
(1)
generalization ability
(1)
bayesian inference
(1)
variational inference
(1)
Papers
Flow to the Mode: Mode-Seeking Diffusion Autoencoders for State-of-the-Art Image Tokenization
ICCV 2025
Range, not Independence, Drives Modularity in Biologically Inspired Representations
ICLR 2025
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
RSS 2024
Evaluating Real-World Robot Manipulation Policies in Simulation
CoRL 2024
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
ICML 2024
Disentanglement via Latent Quantization
NeurIPS 2023
Vision-Based Manipulators Need to Also See from Their Hands
ICLR 2022
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise
NeurIPS 2021
On the Role of Data in PAC-Bayes Bounds
AISTATS 2021
Unsupervised Curricula for Visual Meta-Reinforcement Learning
NeurIPS 2019
Unsupervised Learning via Meta-Learning
ICLR 2019