Insights from the NeurIPS 2021 NetHack Challenge

In this report, we summarize the takeaways from the first NeurIPS 2021 NetHack Challenge. Participants were tasked with developing a program or agent that can win (i.e., ‘ascend’ in) the popular dungeon-crawler game of NetHack by interacting with the NetHack Learning Environment (NLE), a scalable, procedurally generated, and challenging Gym environment for reinforcement learning (RL). The challenge showcased community-driven progress in AI with many diverse approaches significantly beating the previously best results on NetHack. Furthermore, it served as a direct comparison between neural (e.g., deep RL) and symbolic AI, as well as hybrid systems, demonstrating that on NetHack symbolic bots currently outperform deep RL by a large margin. Lastly, no agent got close to winning the game, illustrating NetHack’s suitability as a long-term benchmark for AI research

Re-evaluation of diagnostic parameters is crucial for obtaining accurate data on idiopathic pulmonary fibrosis

Background: The FinnishIPF registry is a prospective, longitudinal national registry study on the epidemiology of idiopathic pulmonary fibrosis (IPF). It was designed to describe the characteristics, management and prognosis of prevalent and incident IPF patients. The study was initiated in 2012. Methods: We present here results limited to five university hospitals. Patients with IPF were screened from hospital registries using ICD-10 diagnosis codes J84.1 and J84.9. All patients who gave informed consent were included and evaluated using novel diagnostic criteria. Point prevalence on the 31st of December in 2012 was calculated using the reported population in each university hospital city as the denominator. Results: Patients with ICD-10 codes J84.1 and J84.9 yielded a heterogeneous group - on the basis of patient records assessed by pulmonologists only 20-30 % of the cases were IPF. After clinical, radiological and histological re-evaluation 111 of 123 (90 %) of patients fulfilled the clinical criteria of IPF. The estimated prevalence of IPF was 8.6 cases/100 000. 60.4 % were men. Forty four percent of the patients were never-smokers. At diagnosis, the patients' mean age was 73.5 years and mean FVC was 80.4 % and DLCO 57.3 % of predicted. Conclusions: Our results suggest that hospital registries are inaccurate for epidemiological studies unless patients are carefully re-evaluated. IPF is diagnosed in Finland at a stage when lung function is still quite well preserved. Smoking in patients with IPF was less common than in previous reports.Peer reviewe

The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016

The 2016 speaker recognition evaluation (SRE'16) is the latest edition in the series of benchmarking events conducted by the National Institute of Standards and Technology (NIST). I4U is a joint entry to SRE'16 as the result from the collaboration and active exchange of information among researchers from sixteen Institutes and Universities across 4 continents. The joint submission and several of its 32 sub-systems were among top-performing systems. A lot of efforts have been devoted to two major challenges, namely, unlabeled training data and dataset shift from Switchboard-Mixer to the new Call My Net dataset. This paper summarizes the lessons learned, presents our shared view from the sixteen research groups on recent advances, major paradigm shift, and common tool chain used in speaker recognition as we have witnessed in SRE'16. More importantly, we look into the intriguing question of fusing a large ensemble of sub-systems and the potential benefit of large-scale collaboration.Peer reviewe