Accepted Papers

Spotlight Presentations

• DOG: Discriminator-only Generation (Poster Session 1)

Authors: Franz Rieger, Joergen Kornfeld 

• Multi-scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data (Poster Session 1)

Authors: Gennady Voronov, Rose Lightheart, Joe Davison, Christoph A. Krettler, David Healey, Thomas Butler

• Graph Generation with Destination-Driven Diffusion Mixture (Poster Session 1)

Authors: Jaehyeong Jo, Dongki Kim, Sung Ju Hwang

• Exploring Chemical Space with Score-based Out-of-distribution Generation (Poster Session 1)

Authors: Seul Lee, Jaehyeong Jo, Sung Ju Hwang

• Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation? (Poster Session 1)

Authors: Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke

• Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space (Poster Session 2)

Authors: Gian Marco Visani, Michael Neal Pun, Arman Angaji, Armita Nourmohammad

• Differentiable Multi-Target Causal Bayesian Experimental Design (Poster Session 1)

Authors: Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer

• Do deep learning models really outperform traditional approaches in molecular docking? (Poster Session 1)

Authors: Yuejiang Yu, Shuqi Lu, Zhifeng Gao, Hang Zheng, Guolin Ke

Poster Session 1

• MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation

Authors:  Clement Vignac, Nagham Osman, Laura Toni, Pascal Frossard

• Improving Protein-Peptide Interface Predictions in the Low Data Regime

Authors:  Justin Diamond, Markus Alexander Lill

• Uni-Fold MuSSe: De Novo Protein Complex Prediction with Protein Language Models

Authors:  Jinhua Zhu, Zhenyu He, Ziyao Li, Guolin Ke, Linfeng Zhang

• Probing Graph Representations

Authors:  Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevskia

• A Multi-Omics Visible Deep Network for Drug Activity Prediction

Authors:  Luigi Ferraro, Giovanni Scala, Luigi Cerulo, Emanuele Carosati, Michele Ceccarelli

• Flexible Small-Molecule Design and Optimization with Equivariant Diffusion Models

Authors:  Charles Harris, Kieran Didi, Arne Schneuing, Yuanqi Du, Arian Rokkum Jamasb, Michael M. Bronstein, Bruno Correia, Pietro Lio, Tom Leon Blundell

• Towards antigenic peptide discovery with better MHC-I binding prediction and improved benchmark methodology

Authors:  Stanisław Gizinski, Grzegorz Preibisch, Piotr Kucharski, Michał Tyrolski, Michał Rembalski, Piotr Grzegorczyk, Anna Gambin

• PF-ABGen: A Reliable and Efficient Antibody Generator via Poisson Flow

Authors:  Chutian Huang, Zijing Liu, Shengyuan Bai, Linwei Zhang, Chencheng Xu, Zhe Wang, Yang Xiang, Yuanpeng Xiong

• DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models

Authors:  Mohamed Amine Ketata, Cedrik Laue, Ruslan Mammadov, Hannes Stark, Menghua Wu, Gabriele Corso, Coline Marquet, Regina Barzilay, Tommi S. Jaakkola

• PocketNet: Ligand-Guided Pocket Prediction for Blind Docking

Authors:  Matthew Masters, Amr H Mahmoud, Markus Alexander Lill

• Accurate Free Energy Estimations of Molecular Systems Via Flow-based Targeted Free Energy Perturbation

Authors:  Soo Jung Lee, Amr H Mahmoud, Markus Alexander Lill

• Domain-aware representation of small molecules for explainable property prediction models

Authors:  Sarveswara Rao Vangala, Sowmya Ramaswamy Krishnan, Navneet Bung, Rajgopal Srinivasan, Arijit Roy

• LEA: Latent Eigenvalue Analysis in application to high-throughput phenotypic drug screening

Authors:  Jiqing Wu, Viktor Koelzer

• SmilesFormer: Language Model for Molecular Design

Authors:  Joshua Owoyemi, Nazim Medzhidov

• RetroG: Retrosynthetic Planning with Tree Search and Graph Learning

Authors:  Stephen Obonyo, Nicolas Jouandeau, Dickson Owuor

• An Exploration of Conditioning Methods in Graph Neural Networks

Authors:  Yeskendir Koishekenov, Erik J Bekkers

• GCI: A (G)raph (C)oncept (I)nterpretation Framework

Authors:  Dmitry Kazhdan, Botty Dimanov, Lucie Charlotte Magister, Pietro Barbiero, Mateja Jamnik, Pietro Lio

• Structure-Based Drug Design via Semi-Equivariant Conditional Normalizing Flows

Authors:  Eyal Rozenberg, Ehud Rivlin, Daniel Freedman

• The Power of Motifs as Inductive Bias for Learning Molecular Distributions

Authors:  Johanna Sommer, Leon Hetzel, David Lodke, Fabian J Theis, Stephan Gonnemann

• Predicting protein stability changes under multiple amino acid substitutions using equivariant graph neural networks

Authors:  Sebastien Boyer, Sam Money-Kyrle, Oliver Bent

• Epigenomic Language Models Powered By Cerebras

Authors:  Meredith Trotter, Cuong Quoc Nguyen, Stephen Young, Rob Woodruff, Kim Branson


Poster Session 2

• EurNet: Efficient Multi-Range Relational Modeling of Protein Structure

Authors:  Minghao Xu, Yuanfan Guo, Yi Xu, Jian Tang, Xinlei Chen, Yuandong Tian

• Enhancing Protein Language Model with Structure-based Encoder and Pre-training

Authors:  Zuobai Zhang, Minghao Xu, Aurelie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang

• GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion

Authors:  Alex M Tseng, Nathaniel Lee Diamant, Tommaso Biancalani, Gabriele Scalia

• Geometry-Complete Diffusion for 3D Molecule Generation

Authors:  Alex Morehead, Jianlin Cheng

• Multiparameter Persistent Homology for Molecular Property Prediction

Authors:  Andac Demir, Bulent Kiziltan

• Learning Protein Family Manifolds with Smoothed Energy-based Models

Authors:  Nathan C. Frey, Dan Berenberg, Joseph Kleinhenz, Stephen Ra, Isidro Hotzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi

• Improving Small Molecule Generation using Mutual Information Machine

Authors:  Danny Reidenbach, Micha Livne, Rajesh K. Ilango, Michelle Lynn Gill, Johnny Israeli

• SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers

Authors:  Michael Maser, Ji Won Park, Joshua Yao-Yu Lin, Jae Hyeon Lee, Nathan C. Frey, Andrew Martin Watkins

• Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration

Authors:  Xiangyu Zhao, Hannes Stark, Dominique Beaini, Yiren Zhao, Pietro Lio

• Improving Graph Generation by Restricting Graph Bandwidth

Authors:  Nathaniel Lee Diamant, Alex M Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia

• FlexVDW: A machine learning approach to account for protein flexibility in ligand docking

Authors:  Patricia Adriana Suriana, Joseph M Paggi, Ron O. Dror

• Accelerating Antimicrobial Peptide Discovery with Latent  Sequence-Structure Model

Authors:  Danqing Wang, Zeyu Wen, Fei YE, Lei Li, Hao Zhou

• EigenFold: Generative Protein Structure Prediction with Diffusion Models

Authors:  Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi S. Jaakkola

• LEP-AD: Language Embeddings of Proteins and Attention to Drugs predicts drug target interactions

Authors:  Anuj Daga, Sumeer Khan, David Gomez Cabrero, Robert Hoehndorf, Narsis A. Kiani, Jesper Tegnar

• Molecular Fragment-based Diffusion Model for Drug Discovery

Authors:  Daniel Levy, Jarrid Rector-Brooks

• Generating Multi-Step Chemical Reaction Pathways with Black-Box Optimization

Authors:  Danny Reidenbach, Connor W. Coley, Kevin Yang

• HiGeN: Hierarchical Multi-resoultion Graph Generative Network

Authors:  Mahdi Karami, Jun Luo

• Evaluating Prompt Tuning for Conditional Protein Sequence Generation

Authors:  Andrea Nathansen, Kevin Klein, Bernhard Y Renard, Melania Nowicka, Jakub M Bartoszewicz

• MoDTI: Modular Framework For Evaluating Inductive Biases in DTI Modeling

Authors: Roy Henha Eyono, Prudencio Tossou, Cas Wognum, Emmanuel Noutahi

  MLDD Workshop - ICLR 2023