Alert button

"Time": models, code, and papers
Alert button

Physics-Aware Recurrent Convolutional (PARC) Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials

Apr 04, 2022
Phong C. H. Nguyen, Joseph B. Choi, Yen-Thi Nguyen, Pradeep K. Seshadri, H. S. Udaykumar, Stephen Baek

Figure 1 for Physics-Aware Recurrent Convolutional (PARC) Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials
Figure 2 for Physics-Aware Recurrent Convolutional (PARC) Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials
Figure 3 for Physics-Aware Recurrent Convolutional (PARC) Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials
Figure 4 for Physics-Aware Recurrent Convolutional (PARC) Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials
Viaarxiv icon

Towards Real-time Semantic RGB-D SLAM in Dynamic Environments

Apr 03, 2021
Tete Ji, Chen Wang, Lihua Xie

Figure 1 for Towards Real-time Semantic RGB-D SLAM in Dynamic Environments
Figure 2 for Towards Real-time Semantic RGB-D SLAM in Dynamic Environments
Figure 3 for Towards Real-time Semantic RGB-D SLAM in Dynamic Environments
Figure 4 for Towards Real-time Semantic RGB-D SLAM in Dynamic Environments
Viaarxiv icon

RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion

Mar 17, 2022
Kai Chen, Ye Wang, Yitong Li, Aiping Li

Figure 1 for RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion
Figure 2 for RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion
Figure 3 for RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion
Figure 4 for RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion
Viaarxiv icon

PARAFAC2$\times$N: Coupled Decomposition of Multi-modal Data with Drift in N Modes

May 06, 2022
Michael D. Sorochan Armstrong, Jesper Løve Hinrich, A. Paulina de la Mata, James J. Harynuk

Figure 1 for PARAFAC2$\times$N: Coupled Decomposition of Multi-modal Data with Drift in N Modes
Figure 2 for PARAFAC2$\times$N: Coupled Decomposition of Multi-modal Data with Drift in N Modes
Figure 3 for PARAFAC2$\times$N: Coupled Decomposition of Multi-modal Data with Drift in N Modes
Figure 4 for PARAFAC2$\times$N: Coupled Decomposition of Multi-modal Data with Drift in N Modes
Viaarxiv icon

Class Balanced PixelNet for Neurological Image Segmentation

Apr 23, 2022
Mobarakol Islam, Hongliang Ren

Figure 1 for Class Balanced PixelNet for Neurological Image Segmentation
Figure 2 for Class Balanced PixelNet for Neurological Image Segmentation
Figure 3 for Class Balanced PixelNet for Neurological Image Segmentation
Figure 4 for Class Balanced PixelNet for Neurological Image Segmentation
Viaarxiv icon

TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models

Apr 29, 2022
Joel Jang, Seonghyeon Ye, Changho Lee, Sohee Yang, Joongbo Shin, Janghoon Han, Gyeonghun Kim, Minjoon Seo

Figure 1 for TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Figure 2 for TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Figure 3 for TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Figure 4 for TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Viaarxiv icon

Industry-academia research collaboration and knowledge co-creation: Patterns and anti-patterns

Apr 29, 2022
Dusica Marijan, Sagar Sen

Figure 1 for Industry-academia research collaboration and knowledge co-creation: Patterns and anti-patterns
Figure 2 for Industry-academia research collaboration and knowledge co-creation: Patterns and anti-patterns
Figure 3 for Industry-academia research collaboration and knowledge co-creation: Patterns and anti-patterns
Figure 4 for Industry-academia research collaboration and knowledge co-creation: Patterns and anti-patterns
Viaarxiv icon

Incident duration prediction using a bi-level machine learning framework with outlier removal and intra-extra joint optimisation

May 18, 2022
Artur Grigorev, Adriana-Simona Mihaita, Seunghyeon Lee, Fang Chen

Figure 1 for Incident duration prediction using a bi-level machine learning framework with outlier removal and intra-extra joint optimisation
Figure 2 for Incident duration prediction using a bi-level machine learning framework with outlier removal and intra-extra joint optimisation
Figure 3 for Incident duration prediction using a bi-level machine learning framework with outlier removal and intra-extra joint optimisation
Figure 4 for Incident duration prediction using a bi-level machine learning framework with outlier removal and intra-extra joint optimisation
Viaarxiv icon

Nightly Automobile Claims Prediction from Telematics-Derived Features: A Multilevel Approach

May 10, 2022
Allen R. Williams, Yoolim Jin, Anthony Duer, Tuka Alhanai, Mohammad Ghassemi

Figure 1 for Nightly Automobile Claims Prediction from Telematics-Derived Features: A Multilevel Approach
Figure 2 for Nightly Automobile Claims Prediction from Telematics-Derived Features: A Multilevel Approach
Figure 3 for Nightly Automobile Claims Prediction from Telematics-Derived Features: A Multilevel Approach
Figure 4 for Nightly Automobile Claims Prediction from Telematics-Derived Features: A Multilevel Approach
Viaarxiv icon

GDGRU-DTA: Predicting Drug-Target Binding Affinity Based on GNN and Double GRU

Apr 25, 2022
Lyu Zhijian, Jiang Shaohua, Liang Yigao, Gao Min

Figure 1 for GDGRU-DTA: Predicting Drug-Target Binding Affinity Based on GNN and Double GRU
Figure 2 for GDGRU-DTA: Predicting Drug-Target Binding Affinity Based on GNN and Double GRU
Figure 3 for GDGRU-DTA: Predicting Drug-Target Binding Affinity Based on GNN and Double GRU
Figure 4 for GDGRU-DTA: Predicting Drug-Target Binding Affinity Based on GNN and Double GRU
Viaarxiv icon