LoG

About LoG

LoG is an annual research conference that covers areas broadly related to machine learning on graphs and geometry, with a special focus on review quality. In its inaugural edition, LoG 2022 received 250+ paper submissions, 2,800+ total registrations, and distributed $30,000+ in reviewer awards. Prior to this, graph learning research was largely presented within broader AI and ML conferences, such as NeurIPS, ICML, and ICLR. The establishment of LoG was intended to consolidate this work in a focused conference, allowing for deeper engagement within the graph community.

The inaugural LoG Conference took place online due to the global pandemic, which allowed for a more accessible, international gathering. The conference received significant attention, reflecting the rapid growth and interest in graph neural networks and geometric learning fields. Keynote speakers from both academia and industry provided overviews of emerging trends and challenges specific to graph learning. As global restrictions eased, LoG adopted a hybrid format, enabling both in-person and virtual attendance. This move was instrumental in fostering international participation, with satellite events and meetups, such as the 2023 LoG meetup in Shanghai, helping build and strengthen local research communities worldwide.

LoG 2024 Suzhou Meetup @ Duke Kunshan University

The Log 2024 Suzhou Meetup will take place @ Duke Kunshan University ⊆ Kunshan ⊆ Suzhou ⊆ Jiangsu ⊆ China. This event aims to bring together experts in geometric deep learning, learning on graphs, and AI for science, fostering communication and collaboration in this cutting edge research area. We look forward to welcoming both established leaders and emerging talents from across the Asia-Pacific region.