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Paavo Parmas — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Paavo Parmas
9
papers ·
17
citations ·
3
h-index
The University of Tokyo
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Neural Replicator Dynamics
2019 · 13 citations
A unified view of likelihood ratio and reparameterization gradients and an optimal importance sampling scheme
2019 · 2 citations
A unified view of likelihood ratio and reparameterization gradients
2021 · 2 citations
Emergence of Exploration in Policy Gradient Reinforcement Learning via Retrying
2026
On Advantage Estimates for Max@K Policy Gradients
2026
Does "Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients?
2026
Double Horizon Model-Based Policy Optimization
2025
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
2019
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
2024
Top co-authors
Yutaka Matsuo
· 4
Masashi Sugiyama
· 2
Shin Ishii
· 2
Soichiro Nishimori
· 2
Tadashi Kozuno
· 2
Toshinori Kitamura
· 2
Akihiro Kubo
· 1
Audrunas Gruslys
· 1
Carl Edward Rasmussen
· 1
Daniel Hennes
· 1
Dustin Morrill
· 1
Edgar Duenez-Guzman
· 1
Topics
Policy Gradient
cs.LG
cs.AI
Model-Based RL
cs.CL
cs.RO
Value-Based
Multi-Agent
Game AI
Exploration