Update publications

Author: divyansha1115

publications.html

@@ -107,7 +107,11 @@ <h4><strong><span style="text-decoration: underline;">Preprints</span></strong><
 </ul>
 <h4><strong><span style="text-decoration: underline;">2025</span></strong></h4><div id="gsc_oci_title_wrapper">
 <ul>
- 	 <li>V Arora, D Lachi, IJ Knight, M Azabou, BA Richards, CL Hurwitz, J Siegle, EL Dyer. <a href="https://arxiv.org/abs/2507.02771"><strong>Know Thyself by Knowing Others: Learning Neuron Identity from Population Context</strong></a> to appear at NeurIPS 2025<span style="color: #008b8b;"><strong>[NeurIPS 2025]</strong></span></li>
+  <li>V. Arora, D. Lachi, I. J. Knight, M. Azabou, B. Richards, C. Hurwitz, J. Siegle, E. Dyer. <strong><a href="https://neurips.cc/virtual/2025/poster/115008">Know Thyself by Knowing Others: Learning Neuron Identity from Population Context</a></strong>, The Thirty-Ninth Annual Conference on Neural Information Processing Systems, 2025. <span style="color: #008b8b;"><strong>[NeurIPS 2025]</strong></span></li>
+  <li>D. Lachi, M. Mohammadi, J. Meyer, V. Arora, T. Palczewski,  E. Dyer. <strong><a href="https://openreview.net/forum?id=fcVIJ2WSIX">RGP: A Cross-Attention based Graph Transformer for Relational Deep Learning</a></strong>, The Fourth Learning on Graphs Conference, 2025. <span style="color: #008b8b;"><strong>[LOG 2025]</strong></span></li>
+  <li>V. Arora*, D. Lachi*, S. P. Mahato, M. Azabou, Z. Chen, E. Dyer. <strong><a href="https://neurips.cc/virtual/2025/127666">Exploiting All Laplacian Eigenvectors for Node Classification with Graph Transformers</a></strong>, New Perspectives in Graph Machine Learning (NeurIPS workshop), 2025. <span style="color: #008b8b;"><strong>[NPGML 2025]</strong></span></li>
+  <li>J. Meyer*, D. Lachi*, M. Mohammadi, R. R. Upendra,  E. Dyer, M Li, T. Palczewski. <strong><a href="https://neurips.cc/virtual/2025/127657">RELATE: A Schema-Agnostic Cross-Attention Encoder for Multimodal Relational Graphs</a></strong>, New Perspectives in Graph Machine Learning (NeurIPS workshop), 2025. <span style="color: #008b8b;"><strong>[NPGML 2025]</strong></span></li>
+  <li>N. Ahad, E.L. Dyer, K.B. Hengen, Y. Xie, M.A. Davenport. <strong><a href="https://arxiv.org/abs/2202.04000">Learning Sinkhorn divergences for supervised change point detection</a></strong>, IEEE Transactions on Signal Processing, August 2025. <span style="color: #008b8b;"><strong>[IEEE-TSP]</strong></span></li>
    <li>Ryoo AH*, Krishna NH*, Mao X*, Azabou M, Dyer EL, Perich MG, Lajoie G. <a href="https://arxiv.org/abs/2506.05320"><strong>Generalizable, real-time neural decoding with hybrid state-space models.</strong></a>, arXiv preprint arXiv:2506.05320, to appear at NeurIPS 2025<span style="color: #008b8b;"><strong>[NeurIPS 2025]</strong></span></li>
   <li>G Mentzelopoulos, I Asmanis, K Kording, EL Dyer, K Daniilidis, F Vitale: A Scalable, Causal, and Energy Efficient Framework for Neural Decoding with Spiking Neural Networks, to appear at NeurIPS 2025<span style="color: #008b8b;"><strong>[NeurIPS 2025]</strong></span></li>
   <li>N. Ahad, E.L. Dyer, K.B. Hengen, Y. Xie, M.A. Davenport. <strong><a href="https://arxiv.org/abs/2202.04000">Learning Sinkhorn divergences for supervised change point detection</a></strong>, IEEE Transactions on Signal Processing, August 2025. <span style="color: #008b8b;"><strong>[IEEE-TSP]</strong></span></li>