Nazi human experimentation

Nazi human experimentation was a series of medical experiments on prisoners by Nazi Germany in its concentration camps mainly between 1942 and 1945. There were at least 15,754 documented victims from a variety of nationalities and age groups, although the plurality were young adults at the time of the experiment. Although most victims survived, many suffered disability as a result. Nazi physicians and their assistants forced prisoners into participating; they did not willingly volunteer and no consent was given for the procedures. Typically, the experiments were conducted without anesthesia and resulted in death, trauma, disfigurement, mutilation, or permanent disability, and as such are considered examples of medical torture. At Auschwitz and other camps, under the direction of Eduard Wirths, selected inmates were subjected to various experiments that were designed to help German military personnel in combat situations, develop new weapons, aid in the recovery of military personnel who had been injured, and to advance Nazi racial ideology and eugenics, including the twin experiments of Josef Mengele. Aribert Heim conducted similar medical experiments at Mauthausen. After the war, these crimes were tried at what became known as the Doctors' Trial, and revulsion at the abuses perpetrated led to the development of the Nuremberg Code of medical ethics. The Nazi physicians in the Doctors' Trial argued that military necessity justified their experiments, and compared their victims to collateral damage from Allied bombings. The table of contents of a document from the Subsequent Nuremberg trials prosecution includes titles of the sections that document medical experiments revolving around: food, seawater, epidemic jaundice, sulfanilamide, blood coagulation and phlegmon. According to the indictments at the subsequent Nuremberg Trials, these experiments included the following: Sigmund Rascher experimented with the effects of Polygal, a substance made from beet and apple pectin, which aided blood clotting.

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari, Danya Li

Deep motion forecasting models have achieved great success when trained on a massive amount of data. Yet, they often perform poorly when training data is limited. To address this challenge, we propose a transfer learning approach for efficiently adapting p ...

2022

Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting

Alexandre Massoud Alahi, Parth Ashit Kothari

Human trajectory forecasting in crowds presents the challenges of modelling social interactions and outputting collision-free multimodal distribution. Following the success of Social Generative Adversarial Networks (SGAN), recent works propose various GAN- ...

2022

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting

A fibre optic and machine learning based health monitoring system for superconducting power applications in modern supergrids

A fibre optic and machine learning based health monitoring system for superconducting power applications in modern supergrids

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting