research
∙
06/05/2023
Neuralangelo: High-Fidelity Neural Surface Reconstruction
Neural surface reconstruction has been shown to be powerful for recoveri...
share
research
∙
03/24/2023
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects
We present a near real-time method for 6-DoF tracking of an unknown obje...
research
∙
01/31/2023
Reinforcement learning and decision making via single-photon quantum walks
Variational quantum algorithms represent a promising approach to quantum...
research
∙
10/18/2022
Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation
We present a parallelized optimization method based on fast Neural Radia...
research
∙
09/05/2022
Multi-Tracer Groundwater Dating in Southern Oman using Bayesian Modelling
In the scope of assessing aquifer systems in areas where freshwater is s...
research
∙
06/15/2022
Variable Bitrate Neural Fields
Neural approximations of scalar and vector fields, such as signed distan...
research
∙
04/22/2022
Zero and Few-shot Learning for Author Profiling
Author profiling classifies author characteristics by analyzing how lang...
research
∙
04/20/2022
Active Few-Shot Learning with FASL
Recent advances in natural language processing (NLP) have led to strong ...
research
∙
03/28/2022
Few-Shot Learning with Siamese Networks and Label Tuning
We study the problem of building text classifiers with little or no trai...
research
∙
01/16/2022
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Neural graphics primitives, parameterized by fully connected neural netw...
research
∙
11/25/2021
Path Guiding Using Spatio-Directional Mixture Models
We propose a learning-based method for light-path construction in path t...
research
∙
11/24/2021
Extracting Triangular 3D Models, Materials, and Lighting From Images
We present an efficient method for joint optimization of topology, mater...
research
∙
09/09/2021
MATE: Multi-view Attention for Table Transformer Efficiency
This work presents a sparse-attention Transformer architecture for model...
research
∙
08/11/2021
Dynamic Diffuse Global Illumination Resampling
Interactive global illumination remains a challenge in radiometrically- ...
research
∙
06/23/2021
Real-time Neural Radiance Caching for Path Tracing
We present a real-time neural radiance caching method for path-traced gl...
research
∙
06/01/2021
DoT: An efficient Double Transformer for NLP tasks with tables
Transformer-based approaches have been successfully used to obtain state...
research
∙
04/02/2021
TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training
We present the TAPAS contribution to the Shared Task on Statement Verifi...
research
∙
03/22/2021
Open Domain Question Answering over Tables via Dense Retrieval
Recent advances in open-domain QA have led to strong models based on den...
research
∙
10/14/2020
Collective defense of honeybee colonies: experimental results and theoretical modeling
Social insect colonies routinely face large vertebrate predators, agains...
research
∙
10/01/2020
Understanding tables with intermediate pre-training
Table entailment, the binary classification task of finding if a sentenc...
research
∙
06/02/2020
Neural Control Variates
We propose neural control variates (NCV) for unbiased variance reduction...
research
∙
04/05/2020
TAPAS: Weakly Supervised Table Parsing via Pre-training
Answering natural language questions over tables is usually seen as a se...
research
∙
04/01/2020
Development of swarm behavior in artificial learning agents that adapt to different foraging environments
Collective behavior, and swarm formation in particular, has been studied...
research
∙
10/15/2019
How a minimal learning agent can infer the existence of unobserved variables in a complex environment
According to a mainstream position in contemporary cognitive science and...
research
∙
08/30/2019
Answering Conversational Questions on Structured Data without Logical Forms
We present a novel approach to answering sequential questions based on s...
research
∙
08/11/2018
Neural Importance Sampling
We propose to use deep neural networks for generating samples in Monte C...
research
∙
12/04/2017
Modelling collective motion based on the principle of agency
Collective motion is an intriguing phenomenon, especially considering th...
research
∙
09/15/2017
