Skip to content
View mkofinas's full-sized avatar
💭
Embarked on a journey to engineer intelligence
💭
Embarked on a journey to engineer intelligence

Highlights

  • Pro

Block or report mkofinas

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
mkofinas/README.md

Hi there 👋

My name is Miltiadis (Miltos) Kofinas, and I am a PhD student in the Video & Image Sense Lab at the University of Amsterdam, supervised by Efstratios Gavves. My research focuses on future spatio-temporal forecasting, with applications on forecasting for autonomous vehicles. My research interests include graph neural networks, neural fields, and geometric deep learning.

Prior to my PhD, I received a Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki. For my Diploma thesis, I researched the topic of Scene Graph Generation using Graph Neural Networks, supervised by Christos Diou and Anastasios Delopoulos. During my studies, I was a computer vision & machine learning engineer at P.A.N.D.O.R.A. Robotics.

Research 🧪 🔬 🖥️

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
Miltiadis Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, David W. Zhang
ICLR 2024 (Oral)
Paper: https://arxiv.org/abs/2403.12143
Source code: https://github.com/mkofinas/neural-graphs
How to Train Neural Field Representations: A Comprehensive Study and Benchmark
Samuele Papa, Riccardo Valperga, David M Knigge, Miltiadis Kofinas, Phillip Lippe, Jan-Jakob Sonke, Efstratios Gavves
CVPR 2024
Paper: https://arxiv.org/abs/2312.10531
Source code: https://github.com/samuelepapa/fit-a-nef
Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
Miltiadis Kofinas, Erik J Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves
NeurIPS 2023
Paper: https://arxiv.org/abs/2310.20679
Source code: https://github.com/mkofinas/aether
Graph Switching Dynamical Systems
Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Efstratios Gavves
ICML 2023
Paper: https://arxiv.org/abs/2306.00370
Source code: https://github.com/yongtuoliu/Graph-Switching-Dynamical-Systems
Roto-translated Local Coordinate Frames for Interacting Dynamical Systems
Miltiadis Kofinas, Naveen Shankar Nagaraja, Efstratios Gavves
NeurIPS 2021
Paper: https://arxiv.org/abs/2110.14961
Source code: https://github.com/mkofinas/locs

Pinned Loading

  1. locs locs Public

    Official source code for "Roto-translated Local Coordinate Frames For Interacting Dynamical Systems". In NeurIPS 2021.

    Python 21 1

  2. aether aether Public

    Official source code for "Latent Field Discovery in Interacting Dynamical Systems with Neural Fields". In NeurIPS 2023.

    Python 6

  3. neural-graphs neural-graphs Public

    Official source code for "Graph Neural Networks for Learning Equivariant Representations of Neural Networks". In ICLR 2024 (oral).

    Python 69 5