COMPUTING WATERTIGHT VOLUMETRIC MODELS FROM BOUNDARY REPRESENTATIONS TO ENSURE CONSISTENT TOPOLOGICAL OPERATIONS

To simulate environmental processes, noise, flooding in cities as well as the behaviour of buildings and infrastructure, ‘watertight’ volumetric models are a measuring prerequisite. They ensure topologically consistent 3D models and allow the definition of proper topological operations. However, in many existing city or other geo-information models, topologically unchecked boundary representations are used to store spatial entities. In order to obtain consistent topological models, including their ‘fillings’, in this paper, a triangulation combined with overlay and path-finding methods is presented by climbing up the dimension, beginning with the wireframe model. The algorithms developed for this task are presented, whereby using the philosophy of graph databases and the Property Graph Model. Examples to illustrate the algorithms are given, and experiments are performed on a data-set from Erfurt, Thuringia (Germany), providing complex geometries of buildings. The heavy influence of double precision arithmetic on the results, in particular the positional and angular precision, is discussed in the end.

Bulk reconstruction and Bogoliubov transformations in AdS2

In the bulk reconstruction program, one constructs boundary representations of bulk fields. We investigate the relation between the global/Poincare and AdS-Rindler representations for AdS2. We obtain the AdS-Rindler smearing function for massive and massless fields and show that the global and AdS-Rindler boundary representations are related by conformal transformations. We also use the boundary representations of creation and annihilation operators to compute the Bogoliubov transformation relating global modes to AdS-Rindler modes for both massive and massless particles.

SpanBERT: Improving Pre-training by Representing and Predicting Spans

We present SpanBERT, a pre-training method that is designed to better represent and predict spans of text. Our approach extends BERT by (1) masking contiguous random spans, rather than random tokens, and (2) training the span boundary representations to predict the entire content of the masked span, without relying on the individual token representations within it. SpanBERT consistently outperforms BERT and our better-tuned baselines, with substantial gains on span selection tasks such as question answering and coreference resolution. In particular, with the same training data and model size as BERTlarge, our single model obtains 94.6% and 88.7% F1 on SQuAD 1.1 and 2.0 respectively. We also achieve a new state of the art on the OntoNotes coreference resolution task (79.6% F1), strong performance on the TACRED relation extraction benchmark, and even gains on GLUE. 1

Some spherical functions on hyperbolic groups

We investigate properties of some spherical functions defined on hyperbolic groups using boundary representations on the Gromov boundary endowed with the Patterson–Sullivan measure class. We prove sharp decay estimates for spherical functions as well as spectral inequalities associated with boundary representations. This point of view on the boundary allows us to view the so-called property RD (also called Haagerup’s inequality) as a particular case of a more general behavior of spherical functions on hyperbolic groups. We also prove that the family of boundary representations studied in this paper, which can be regarded as a one parameter deformation of the boundary unitary representation, are slow growth representations acting on a Hilbert space admitting a proper 1-cocycle.