# Multitask Extension of Geometrically Aligned Transfer Encoder

arXiv: https://arxiv.org/abs/2405.01974 · HTML: https://mlsanity.com/paper/2405.01974/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 23 references that are in the map.
- First posted on arXiv 3 May 2024.

## Builds on (most cited first, 7 of 7)

- [Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering](https://mlsanity.com/paper/1606.09375/) (2016)
- [Spectral Networks and Locally Connected Networks on Graphs](https://mlsanity.com/paper/1312.6203/) (2013)
- [Convolutional Networks on Graphs for Learning Molecular Fingerprints](https://mlsanity.com/paper/1509.09292/) (2015)
- [Analyzing Learned Molecular Representations for Property Prediction](https://mlsanity.com/paper/1904.01561/) (2019)
- [Learning Multimodal Graph-to-Graph Translation for Molecular Optimization](https://mlsanity.com/paper/1812.01070/) (2018)
- [Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks](https://mlsanity.com/paper/2310.06369/) (2023)
- [Grouping-matrix based Graph Pooling with Adaptive Number of Clusters](https://mlsanity.com/paper/2209.02939/) (2022)

## Built on by (most cited first, 3 of 3)

- [Task Addition in Multi-Task Learning by Geometrical Alignment](https://mlsanity.com/paper/2409.16645/) (2024)
- [Geometric Embedding Alignment via Curvature Matching in Transfer Learning](https://mlsanity.com/paper/2506.13015/) (2025)
- [Towards a Generalizable AI for Materials Discovery: Validation through Immersion Coolant Screening](https://mlsanity.com/paper/2510.23371/) (2025)

## Abstract (arXiv)

Molecular datasets often suffer from a lack of data. It is well-known that gathering data is difficult due to the complexity of experimentation or simulation involved. Here, we leverage mutual information across different tasks in molecular data to address this issue. We extend an algorithm that utilizes the geometric characteristics of the encoding space, known as the Geometrically Aligned Transfer Encoder (GATE), to a multi-task setup. Thus, we connect multiple molecular tasks by aligning the curved coordinates onto locally flat coordinates, ensuring the flow of information from source tasks to support performance on target data.