activity
20132026
most citedAutoCompete: A Framework for Machine Learning Competition

9 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

MedCalc-Bench Doesn't Measure What You Think: A Benchmark Audit and the Case for Open-Book Evaluation

Artus Krohn-Grimberghe

MedCalc-Bench is a widely used benchmark for evaluating LLM performance on clinical calculator tasks, with state-of-the-art direct prompting scores plateauing around 35% on the Ver…

cs.CV2018★ 2 cited

Multi-Stage Reinforcement Learning For Object Detection

Jonas Koenig, Simon Malberg, Martin Martens +3

We present a reinforcement learning approach for detecting objects within an image. Our approach performs a step-wise deformation of a bounding box with the goal of tightly framing…

cs.CV2017★ 7 cited

Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet

Naimish Agarwal, Artus Krohn-Grimberghe, Ranjana Vyas

Facial Key Points (FKPs) Detection is an important and challenging problem in the fields of computer vision and machine learning. It involves predicting the co-ordinates of the FKP…

stat.ML2015★ 9 cited

AutoCompete: A Framework for Machine Learning Competition

Abhishek Thakur, Artus Krohn-Grimberghe

In this paper, we propose AutoCompete, a highly automated machine learning framework for tackling machine learning competitions. This framework has been learned by us, validated an…

cs.CY2013★ 7 cited

Practical Aspects of the Bitcoin System

Artus Krohn-Grimberghe Christoph Sorge

Digital payment schemes show an ever increasing importance. Out of the countless different schemes available this article focuses on the popular Bitcoin system. The authors provide…