2 papers
cs.LG2026
Tight Sample Complexity Bounds for Entropic Best Policy Identification
Amer Essakine, Claire Vernade
We study best-policy identification for finite-horizon risk-sensitive reinforcement learning under the entropic risk measure. Recent work established a constant gap in the exponent…
cs.CV2025
Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey
Amer Essakine, Yanqi Cheng, Chun-Wun Cheng +5
Implicit Neural Representations (INRs) have emerged as a paradigm in knowledge representation, offering exceptional flexibility and performance across a diverse range of applicatio…