ContrastCAD: Contrastive Learning-based Representation Learning for Computer-Aided Design Models

1 code implementation • 2 Apr 2024 • Minseop Jung, Minseong Kim, Jibum Kim

However, learning CAD models is still a challenge, because they can be represented as complex shapes with long construction sequences.

Contrastive Learning Data Augmentation +1

Mol-AIR: Molecular Reinforcement Learning with Adaptive Intrinsic Rewards for Goal-directed Molecular Generation

1 code implementation • 29 Mar 2024 • Jinyeong Park, Jaegyoon Ahn, Jonghwan Choi, Jibum Kim

We believe that Mol-AIR represents a significant advancement in drug discovery, offering a more efficient path to discovering novel therapeutics.

Drug Discovery reinforcement-learning

A Lightweight CNN-Transformer Model for Learning Traveling Salesman Problems

1 code implementation • 3 May 2023 • Minseop Jung, Jaeseung Lee, Jibum Kim

Experimental results show that the proposed CNN embedding layer and partial self-attention are very effective in improving performance and computational complexity.

Learning Geometric Combinatorial Optimization Problems using Self-attention and Domain Knowledge

1 code implementation • 5 Jul 2021 • Jaeseung Lee, Woojin Choi, Jibum Kim

In the decoder, a new masking scheme using domain knowledge is proposed to provide a high penalty when the geometric requirement of the problem is not satisfied.

Combinatorial Optimization Decoder +1