Patrick van der Smagt
17 papers · 2015–2024 · 8 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+10 more ↓ Show less ↑
🏃 Academic Marathon (9) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (8) 🐣 Hot Topic Early Bird
🌍
Conference Polyglot
(8)
🏃
Academic Marathon
(9)
🧭
Keyword Pioneer
🧬
Topic Evolution
🏆
Grand Slam
🗃️
Keyword Collector
(65)
💎
Century Club
(17)
🔥
Unstoppable
(6)
📈
Trend Setter
🚀
Conference Pioneer
Conferences
NIPS (4)
ICLR (3)
L4DC (3)
CORL (2)
ICML (2)
AAAI (1)
ICCV (1)
RSS (1)
Top co-authors
Keywords
variational inference
(5)
variational autoencoder
(4)
world model
(2)
constrained optimization
(2)
differentiable rendering
(2)
probabilistic inference
(2)
state-space model
(2)
offline reinforcement learning
(1)
metric learning
(1)
reinforcement learning
(1)
pose estimation
(1)
bayesian inference
(1)
multi-source learning
(1)
motion estimation
(1)
sample efficiency
(1)
visual navigation
(1)
video understanding
(1)
policy optimization
(1)
3d vision
(1)
supervised learning
(1)
Papers
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
NIPS 2024
Exploring Under Constraints with Model-Based Actor-Critic and Safety Filters
CORL 2024
CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces
L4DC 2023
Filter-Aware Model-Predictive Control
L4DC 2023
Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models
NIPS 2023
PRISM: Probabilistic Real-Time Inference in Spatial World Models
CORL 2022
Tracking and Planning with Spatial World Models
L4DC 2022
Latent Matters: Learning Deep State-Space Models
NIPS 2021
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
ICLR 2021
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
ICLR 2021
Continual Learning with Bayesian Neural Networks for Non-Stationary Data
ICLR 2020
Learning Flat Latent Manifolds with VAEs
ICML 2020
Approximate Bayesian Inference in Spatial Environments
RSS 2019
Multi-Source Neural Variational Inference
AAAI 2019
Switching Linear Dynamics for Variational Bayes Filtering
ICML 2019
Learning Hierarchical Priors in VAEs
NIPS 2019
FlowNet: Learning Optical Flow With Convolutional Networks
ICCV 2015