research
∙
09/18/2023
One ACT Play: Single Demonstration Behavior Cloning with Action Chunking Transformers
Learning from human demonstrations (behavior cloning) is a cornerstone o...
share
research
∙
09/16/2023
Pour me a drink: Robotic Precision Pouring Carbonated Beverages into Transparent Containers
With the growing emphasis on the development and integration of service ...
research
∙
09/15/2023
SculptBot: Pre-Trained Models for 3D Deformable Object Manipulation
Deformable object manipulation presents a unique set of challenges in ro...
research
∙
09/01/2023
Catalyst Property Prediction with CatBERTa: Unveiling Feature Exploration Strategies through Large Language Models
Efficient catalyst screening necessitates predictive models for adsorpti...
research
∙
08/30/2023
Materials Informatics Transformer: A Language Model for Interpretable Materials Properties Prediction
Recently, the remarkable capabilities of large language models (LLMs) ha...
research
∙
08/04/2023
Fluid Property Prediction Leveraging AI and Robotics
Inferring liquid properties from vision is a challenging task due to the...
research
∙
07/24/2023
RoboChop: Autonomous Framework for Fruit and Vegetable Chopping Leveraging Foundational Models
With the goal of developing fully autonomous cooking robots, developing ...
research
∙
06/28/2023
HNO: Hyena Neural Operator for solving PDEs
Numerically solving partial differential equations (PDEs) typically requ...
research
∙
05/27/2023
Scalable Transformer for PDE Surrogate Modeling
Transformer has shown state-of-the-art performance on various applicatio...
research
∙
05/16/2023
OpenVR: Teleoperation for Manipulation
Across the robotics field, quality demonstrations are an integral part o...
research
∙
05/15/2023
Physics Informed Token Transformer
Solving Partial Differential Equations (PDEs) is the core of many fields...
research
∙
04/10/2023
Neural Network Predicts Ion Concentration Profiles under Nanoconfinement
Modeling the ion concentration profile in nanochannel plays an important...
research
∙
03/13/2023
Transformer-based Planning for Symbolic Regression
Symbolic regression (SR) is a challenging task in machine learning that ...
research
∙
03/03/2023
Denoise Pre-training on Non-equilibrium Molecules for Accurate and Transferable Neural Potentials
Machine learning methods, particularly recent advances in equivariant gr...
research
∙
12/02/2022
MeshDQN: A Deep Reinforcement Learning Framework for Improving Meshes in Computational Fluid Dynamics
Meshing is a critical, but user-intensive process necessary for stable a...
research
∙
11/26/2022
A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction
Machine learning models are gaining increasing popularity in the domain ...
research
∙
10/25/2022
MOFormer: Self-Supervised Transformer model for Metal-Organic Framework Property Prediction
Metal-Organic Frameworks (MOFs) are materials with a high degree of poro...
research
∙
09/22/2022
Minimizing Human Assistance: Augmenting a Single Demonstration for Deep Reinforcement Learning
The use of human demonstrations in reinforcement learning has proven to ...
research
∙
09/19/2022
MAN: Multi-Action Networks Learning
Learning control policies with large action spaces is a challenging prob...
research
∙
09/12/2022
Graph Neural Networks for Molecules
Graph neural networks (GNNs), which are capable of learning representati...
research
∙
09/03/2022
TransPolymer: a Transformer-based Language Model for Polymer Property Predictions
Accurate and efficient prediction of polymer properties is of great sign...
research
∙
07/25/2022
Surrogate Modeling of Melt Pool Thermal Field using Deep Learning
Powder-based additive manufacturing has transformed the manufacturing in...
research
∙
05/26/2022
Transformer for Partial Differential Equations' Operator Learning
Data-driven learning of partial differential equations' solution operato...
research
∙
05/11/2022
Deep-Learned Generators of Porosity Distributions Produced During Metal Additive Manufacturing
Laser Powder Bed Fusion has become a widely adopted method for metal Add...
research
∙
05/04/2022
Crystal Twins: Self-supervised Learning for Crystalline Material Property Prediction
Machine learning (ML) models have been widely successful in the predicti...
research
∙
02/18/2022
Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast
Deep learning has been a prevalence in computational chemistry and widel...
research
∙
01/26/2022
MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning
Characterizing meltpool shape and geometry is essential in metal Additiv...
research
∙
12/06/2021
Graph Neural Networks Accelerated Molecular Dynamics
Molecular Dynamics (MD) simulation is a powerful tool for understanding ...
research
∙
11/30/2021
AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learning
Machine learning (ML) has demonstrated the promise for accurate and effi...
research
∙
07/09/2021
Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid Simulations
Reduced Order Modelling (ROM) has been widely used to create lower order...
research
∙
04/26/2021
Dominant motion identification of multi-particle system using deep learning from video
Identifying underlying governing equations and physical relevant informa...
research
∙
03/15/2021
Deep learning of material transport in complex neurite networks
Neurons exhibit complex geometry in their branched networks of neurites ...
research
∙
03/08/2021
An Energy-Saving Snake Locomotion Gait Policy Using Deep Reinforcement Learning
Snake robots, comprised of sequentially connected joint actuators, have ...
research
∙
02/19/2021
MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks
Molecular machine learning bears promise for efficient molecule property...
research
∙
01/19/2021
Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination
Two-dimensional nanomaterials, such as graphene, have been extensively s...
research
∙
01/12/2021
Airfoil GAN: Encoding and Synthesizing Airfoils forAerodynamic-aware Shape Optimization
The current design of aerodynamic shapes, like airfoils, involves comput...
research
∙
12/03/2020
Graph Convolutional Neural Networks for Body Force Prediction
Many scientific and engineering processes produce spatially unstructured...
research
∙
10/21/2020
Deep Learning for Efficient Reconstruction of High-Resolution Turbulent DNS Data
Within the domain of Computational Fluid Dynamics, Direct Numerical Simu...
research
∙
10/20/2020
Data-driven Identification of 2D Partial Differential Equations using extracted physical features
Many scientific phenomena are modeled by Partial Differential Equations ...
research
∙
10/05/2020
FaultNet: A Deep Convolutional Neural Network for bearing fault classification
The increased presence of advanced sensors on the production floors has ...
research
∙
05/13/2020
Deep Learning Convective Flow Using Conditional Generative Adversarial Networks
We developed a general deep learning framework, FluidGAN, that is capabl...
research
∙
03/18/2020
Potential Neutralizing Antibodies Discovered for Novel Corona Virus Using Machine Learning
The fast and untraceable virus mutations take lives of thousands of peop...
research
∙
01/18/2020
Effects of sparse rewards of different magnitudes in the speed of learning of model-based actor critic methods
Actor critic methods with sparse rewards in model-based deep reinforceme...
research
∙
10/16/2019
Creativity in Robot Manipulation with Deep Reinforcement Learning
Deep Reinforcement Learning (DRL) has emerged as a powerful control tech...
research
∙
07/24/2018
Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss
In typical machine learning tasks and applications, it is necessary to o...
research
∙
03/23/2018
Deep Learning Phase Segregation
Phase segregation, the process by which the components of a binary mixtu...
research
∙
03/12/2018