11 Papers Accepted at NeurIPS 2025!
We are happy to announce that 11 papers from Archimedes, Athena Research Center, Greece, have been accepted at the Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)!
NeurIPS is a major annual event in the artificial intelligence and machine learning community and this year it will take place from December 2 to December 7 at the San Diego Convention Center, California, USA.
Congratulations to our researchers:
Kostas Daniilidis, Vasilis Gkatzelis, Costas Anastassiou, Thodoris Kouzelis, Efstathios Karypidis, Ioannis Kakogeorgiou, Nikos Komodakis, Anastasios Gerontopoulos, Yorgos Pantis, Christos Tzamos, Andreas Kontogiannis, Vasilis Pollatos, Panayotis Mertikopoulos, Ioannis Panageas, Vaggelis Dorovatas, Alexandros Potamianos and Vaggos Chatziafratis!
The accepted papers can be found below:
A Scalable, Causal, and Energy Efficient Framework for Neural Decoding with Spiking Neural Networks,
Mentzelopoulos, G., Asmanis, I., Kording, K., Dyer, E., Kostas Daniilidis, and Vitale, F.
Procurement Auctions with Predictions: Improved Frugality for Facility Location,
E. Balkanski, N. DeFilippis, Vasilis Gkatzelis, and X. Tan
NOBLE - Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models,
Luca Ghafourpour, Valentin Duruisseaux, Bahareh Tolooshams, Philip H. Wong, Costas Anastassiou, Anima Anandkumar
link: https://arxiv.org/pdf/2506.04536
Boosting Generative Image Modeling via Joint Image-Feature Synthesis,
Thodoris Kouzelis, Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris, Nikos Komodakis
link: https://arxiv.org/pdf/2504.16064
DINO-Foresight: Looking into the Future with DINO,
Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris, Nikos Komodakis
link: https://arxiv.org/pdf/2412.11673
Multi-Token Prediction Needs Registers,
Anastasios Gerontopoulos, Spyros Gidaris, Nikos Komodakis
link: https://arxiv.org/pdf/2505.10518
ReplaceMe: Network Simplification via Depth Pruning and Transformer Block Linearization,
Dmitriy Shopkhoev, Ammar Ali, Magauiya Zhussip, Valentin Malykh, Stamatios Lefkimmiatis, Nikos Komodakis, Sergey Zagoruyko
link: https://arxiv.org/pdf/2505.02819
Teaching Transformers to Solve Combinatorial Problems through Efficient Trial & Error,
Panagiotis Giannoulis, Yorgos Pantis, Christos Tzamos
link: https://arxiv.org/pdf/2509.22023
Efficient Kernelized Learning in Polyhedral Games Beyond Full-Information: From Colonel Blotto to Congestion Games,
Andreas Kontogiannis, Vasilis Pollatos, Gabriele Farina, Panayotis Mertikopoulos, Ioannis Panageas
link: https://arxiv.org/pdf/2509.20919
Auto-Compressing Networks,
Vaggelis Dorovatas, Georgios Paraskevopoulos, Alexandros Potamianos
The Complexity of Finding Local Optima in Contrastive Learning,
Jingming Yan, Yiyuan Luo, Vaggos Chatziafratis, Ioannis Panageas, Parnian Shahkar, and Stelios Stavroulakis
link: https://arxiv.org/pdf/2509.16898
