activity
20182021
most citedAn Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries

8 citations · 8 across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG2021

Robust PDF Document Conversion Using Recurrent Neural Networks

Nikolaos Livathinos, Cesar Berrospi, Maksym Lysak +7

The number of published PDF documents has increased exponentially in recent decades. There is a growing need to make their rich content discoverable to information retrieval tools.…

cs.IR20198 cited

An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries

Matteo Manica, Christoph Auer, Valery Weber +9

Information extraction and data mining in biochemical literature is a daunting task that demands resource-intensive computation and appropriate means to scale knowledge ingestion.…

cond-mat.str-el2019

Understanding repulsively mediated superconductivity of correlated electrons via massively parallel DMRG

Adrian Kantian, Michele Dolfi, Matthias Troyer +1

The so-called minimal models of unconventional superconductivity are lattice models of interacting electrons derived from materials in which electron pairing arises from purely rep…

cs.DL2018

Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale

Peter W J Staar, Michele Dolfi, Christoph Auer +1

Over the past few decades, the amount of scientific articles and technical literature has increased exponentially in size. Consequently, there is a great need for systems that can…

cs.DL2018

Corpus Conversion Service: A machine learning platform to ingest documents at scale [Poster abstract]

Peter W J Staar, Michele Dolfi, Christoph Auer +1

Over the past few decades, the amount of scientific articles and technical literature has increased exponentially in size. Consequently, there is a great need for systems that can…