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researcher

João F. Henriques

4 papers hereh-index 225 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG1
  • cs.SE1
same name
  • João F. Henriques — 23 papers, h 31
  • João F. Henriques — 5 papers
  • João F. Henriques — 5 papers, h 1
  • João F. Henriques — 4 papers, h 2
  • João F. Henriques — 4 papers, h 2
  • João F. Henriques — 4 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedLangProp: A code optimization framework using Large Language Models applied to driving

2 citations · 3 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

HiResNets: Native Full-HD Video Recognition with Foveal Residual Streams

Shivani Mall, Swarnim Jain, Joao F. Henriques

Much of the recent progress in image and video recognition has come at the cost of memory: larger models, increased resolution, and longer temporal contexts. An inevitable componen…

cs.CV2025

CRAM: Large-scale Video Continual Learning with Bootstrapped Compression

Shivani Mall, Joao F. Henriques

Continual learning (CL) promises to allow neural networks to learn from continuous streams of inputs, instead of IID (independent and identically distributed) sampling, which requi…

cs.LG2024★ 1 cited

SOAP-RL: Sequential Option Advantage Propagation for Reinforcement Learning in POMDP Environments

Shu Ishida, João F. Henriques

This work compares ways of extending Reinforcement Learning algorithms to Partially Observed Markov Decision Processes (POMDPs) with options. One view of options is as temporally e…

cs.SE2024★ 2 cited

LangProp: A code optimization framework using Large Language Models applied to driving

Shu Ishida, Gianluca Corrado, George Fedoseev +5

We propose LangProp, a framework for iteratively optimizing code generated by large language models (LLMs), in both supervised and reinforcement learning settings. While LLMs can g…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.