Scannet++: A high-fidelity dataset of 3d indoor scenes

C Yeshwanth, YC Liu, M Nießner… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present ScanNet++, a large-scale dataset that couples together capture of high-quality
and commodity-level geometry and color of indoor scenes. Each scene is captured with a …

The falcon series of open language models

E Almazrouei, H Alobeidli, A Alshamsi… - arXiv preprint arXiv …, 2023 - arxiv.org
We introduce the Falcon series: 7B, 40B, and 180B parameters causal decoder-only models
trained on a diverse high-quality corpora predominantly assembled from web data. The …

Diffusion Schrödinger bridge matching

Y Shi, V De Bortoli, A Campbell… - Advances in Neural …, 2024 - proceedings.neurips.cc
Solving transport problems, ie finding a map transporting one given distribution to another,
has numerous applications in machine learning. Novel mass transport methods motivated …

Imitating human behaviour with diffusion models

T Pearce, T Rashid, A Kanervisto, D Bignell… - arXiv preprint arXiv …, 2023 - arxiv.org
Diffusion models have emerged as powerful generative models in the text-to-image domain.
This paper studies their application as observation-to-action models for imitating human …

Evaluation of cell-cell interaction methods by integrating single-cell RNA sequencing data with spatial information

Z Liu, D Sun, C Wang - Genome Biology, 2022 - Springer
Background Cell-cell interactions are important for information exchange between different
cells, which are the fundamental basis of many biological processes. Recent advances in …

Recent advances in optimal transport for machine learning

EF Montesuma, FN Mboula, A Souloumiac - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, Optimal Transport has been proposed as a probabilistic framework in Machine
Learning for comparing and manipulating probability distributions. This is rooted in its rich …

Independent se (3)-equivariant models for end-to-end rigid protein docking

OE Ganea, X Huang, C Bunne, Y Bian… - arXiv preprint arXiv …, 2021 - arxiv.org
Protein complex formation is a central problem in biology, being involved in most of the cell's
processes, and essential for applications, eg drug design or protein engineering. We tackle …

Equivariant flow matching

L Klein, A Krämer, F Noé - Advances in Neural Information …, 2024 - proceedings.neurips.cc
Normalizing flows are a class of deep generative models that are especially interesting for
modeling probability distributions in physics, where the exact likelihood of flows allows …

Multisample flow matching: Straightening flows with minibatch couplings

AA Pooladian, H Ben-Hamu, C Domingo-Enrich… - arXiv preprint arXiv …, 2023 - arxiv.org
Simulation-free methods for training continuous-time generative models construct probability
paths that go between noise distributions and individual data samples. Recent works, such …

Nersemble: Multi-view radiance field reconstruction of human heads

T Kirschstein, S Qian, S Giebenhain, T Walter… - ACM Transactions on …, 2023 - dl.acm.org
We focus on reconstructing high-fidelity radiance fields of human heads, capturing their
animations over time, and synthesizing re-renderings from novel viewpoints at arbitrary time …