Maksim Kuznetsov

Research Scientist at @InSilicoMeds

[Sarath Chandar @apsarathchandar]

I am excited to share that our BindGPT paper won the best poster award at @RealAAAI #AAAI2025! Congratulations to the team! Work led by @artemZholus!

[Maksim Kuznetsov @Max__Kuznetsov]

7/ Finally, nach0-pc enables de novo ligand generation, designing molecules that bind to protein pockets.

[Maksim Kuznetsov @Max__Kuznetsov]

1/ At @InSilicoMeds, we’re exploring how language models can process and generate 3D molecular structures.
nach0-pc fuses a specialized text-based representation with a domain-specific encoder, enabling precise generation and conditioning on 3D molecular structures.

[Maksim Kuznetsov @Max__Kuznetsov]

6/ By injecting noise into point clouds, nach0-pc can generate alternative molecular structures that retain reference molecule shape.

[Maksim Kuznetsov @Max__Kuznetsov]

🎉 Excited to announce that "nach0-pc: Multi-task Language Model with Molecular Point Cloud Encoder" will be presented at @RealAAAI!
#AAAI2025 #AAAI25
📍 Poster #166
🕜 12:30 PM - 2:30 PM, March 1, 2025
📄 Paper: https://t.co/sj5VW3NbfE

[Sarath Chandar @apsarathchandar]

BindGPT is going to be presented at AAAI 25 today.
Work led by my PhD student @artemZholus in collaboration with @InSilicoMeds
Don’t miss 10/10
https://t.co/TjjPoRr38F
https://t.co/8EwV11No2Q
https://t.co/tWvsKqUWuh

[Maksim Kuznetsov @Max__Kuznetsov]

@artemZholus @oliviaviessmann @BiologyAIDaily @FlagshipPioneer In the parallel study (https://t.co/SBcM7Yr7qf), we explored the concept of integrating the point cloud encoder to directly and efficiently (1 embedding by 1 atom) pass spatial molecular structures like protein pockets into the language model's input.

[Maksim Kuznetsov @Max__Kuznetsov]

Excited to present our new paper nach0 from @InSilicoMeds, in collaboration with @nvidia, published in @ChemicalScience:
📄 Paper: https://t.co/WY4Zf3Zf1v
💻 Code: https://t.co/hOGlfJhiEr
🤗 Try it now on @huggingface: https://t.co/bdAo79mPwb

[Maksim Kuznetsov @Max__Kuznetsov]

Our new paper from @InSilicoMeds on neural conformation generation at @JCIM_JCTC
“COSMIC: Molecular Conformation Space Modeling in Internal Coordinates with an Adversarial Framework”

Paper: https://t.co/pJeh4fhJXn
Code: https://t.co/CxExblkbtS

[Maksim Kuznetsov @Max__Kuznetsov]

Happy to present our latest results in
@InSilicoMeds on molecular graph generation at #AAAI2021!
Check out our joint work with @d_polykovskiy “MolGrow: A Graph Normalizing Flow for Hierarchical Molecular Generation” at poster session on
5-Feb, 08:45-10:30 AM & 04:45-06:30 PM PST

[Maksim Kuznetsov @Max__Kuznetsov]

@norpadon Д��я сложных пайплайнов есть ещё https://t.co/1jLnTFdrLT, но его удобность под вопросом

[Maksim Kuznetsov @Max__Kuznetsov]

@norpadon https://t.co/w3OOAwwVBY

[Maksim Kuznetsov @Max__Kuznetsov]

@norpadon Чтобы избавиться от проблем с трейн лупом, наши предки принимали прост��й советский...

[Daniil Polykovskiy @d_polykovskiy]

Our new paper with @InSilicoMeds: "Molecular Generation for Desired Transcriptome Changes With AAE". We propose a joint model that can sample molecules for a given transcriptome change and vise versa.

Paper: https://t.co/GuiEZ9Ce6S
Code: https://t.co/KxHa0ixN94

[Lightning AI ⚡️ @LightningAI]

Molecular Generation for Desired Transcriptome Changes with Adversarial Autoencoders.

"In this paper, we propose a new generative model that infers drug molecules that could induce a desired change in gene expression"

In #pytorch #pytorchLightning
https://t.co/dnwjf7dWHF

[Daniil Polykovskiy @d_polykovskiy]

Check out our #AISTATS paper from @InSilicoMeds: “Deterministic Decoding for Discrete Data in Variational Autoencoders”. Apparently, for lossless decoding, you need bounded support proposals!

https://t.co/Xs30SnmkKk