Neural language representations predict outcomes of scientific research. - James P. Bagrow; Daniel Berenberg; Joshua Clifford Bongard (CoRR, 2018)

Inferring the size of the causal universe: features and fusion of causal attribution networks. - Daniel Berenberg; James P. Bagrow (CoRR, 2018)

Efficient Crowd Exploration of Large Networks: The Case of Causal Attribution. - Daniel Berenberg; James P. Bagrow (Proc. ACM Hum. Comput. Interact., 2018)

Multi-segment preserving sampling for deep manifold sampler. - Daniel Berenberg; Jae Hyeon Lee; Simon Kelow; Ji Won Park; Andrew M. Watkins; Vladimir Gligorijevic; Richard Bonneau; Stephen Ra; Kyunghyun Cho (CoRR, 2022)

OpenProteinSet: Training data for structural biology at scale. - Gustaf Ahdritz; Nazim Bouatta; Sachin Kadyan; Lukas Jarosch; Daniel Berenberg; Ian Fisk; Andrew M. Watkins; Stephen Ra; Richard Bonneau; Mohammed AlQuraishi (NeurIPS, 2023)

Protein Discovery with Discrete Walk-Jump Sampling. - Nathan C. Frey; Daniel Berenberg; Karina Zadorozhny; Joseph Kleinhenz; Julien Lafrance-Vanasse; Isidro Hötzel; Yan Wu 027; Stephen Ra; Richard Bonneau; Kyunghyun Cho; Andreas Loukas; Vladimir Gligorijevic; et al. (ICLR, 2024)