Search Results for author: Alishba Imran

Found 7 papers, 4 papers with code

How GPT learns layer by layer

1 code implementation13 Jan 2025 Jason Du, Kelly Hong, Alishba Imran, Erfan Jahanparast, Mehdi Khfifi, Kaichun Qiao

Understanding how LLMs build internal world models is key to developing agents capable of consistent, adaptive behavior across tasks.

Navigate Representation Learning

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

1 code implementation20 Nov 2024 Yoel Zimmermann, Adib Bazgir, Zartashia Afzal, Fariha Agbere, Qianxiang Ai, Nawaf Alampara, Alexander Al-Feghali, Mehrad Ansari, Dmytro Antypov, Amro Aswad, Jiaru Bai, Viktoriia Baibakova, Devi Dutta Biswajeet, Erik Bitzek, Joshua D. Bocarsly, Anna Borisova, Andres M Bran, L. Catherine Brinson, Marcel Moran Calderon, Alessandro Canalicchio, Victor Chen, Yuan Chiang, Defne Circi, Benjamin Charmes, Vikrant Chaudhary, Zizhang Chen, Min-Hsueh Chiu, Judith Clymo, Kedar Dabhadkar, Nathan Daelman, Archit Datar, Wibe A. de Jong, Matthew L. Evans, Maryam Ghazizade Fard, Giuseppe Fisicaro, Abhijeet Sadashiv Gangan, Janine George, Jose D. Cojal Gonzalez, Michael Götte, Ankur K. Gupta, Hassan Harb, Pengyu Hong, Abdelrahman Ibrahim, Ahmed Ilyas, Alishba Imran, Kevin Ishimwe, Ramsey Issa, Kevin Maik Jablonka, Colin Jones, Tyler R. Josephson, Greg Juhasz, Sarthak Kapoor, Rongda Kang, Ghazal Khalighinejad, Sartaaj Khan, Sascha Klawohn, Suneel Kuman, Alvin Noe Ladines, Sarom Leang, Magdalena Lederbauer, Sheng-Lun, Liao, Hao liu, Xuefeng Liu, Stanley Lo, Sandeep Madireddy, Piyush Ranjan Maharana, Shagun Maheshwari, Soroush Mahjoubi, José A. Márquez, Rob Mills, Trupti Mohanty, Bernadette Mohr, Seyed Mohamad Moosavi, Alexander Moßhammer, Amirhossein D. Naghdi, Aakash Naik, Oleksandr Narykov, Hampus Näsström, Xuan Vu Nguyen, Xinyi Ni, Dana O'Connor, Teslim Olayiwola, Federico Ottomano, Aleyna Beste Ozhan, Sebastian Pagel, Chiku Parida, Jaehee Park, Vraj Patel, Elena Patyukova, Martin Hoffmann Petersen, Luis Pinto, José M. Pizarro, Dieter Plessers, Tapashree Pradhan, Utkarsh Pratiush, Charishma Puli, Andrew Qin, Mahyar Rajabi, Francesco Ricci, Elliot Risch, Martiño Ríos-García, Aritra Roy, Tehseen Rug, Hasan M Sayeed, Markus Scheidgen, Mara Schilling-Wilhelmi, Marcel Schloz, Fabian Schöppach, Julia Schumann, Philippe Schwaller, Marcus Schwarting, Samiha Sharlin, Kevin Shen, Jiale Shi, Pradip Si, Jennifer D'Souza, Taylor Sparks, Suraj Sudhakar, Leopold Talirz, Dandan Tang, Olga Taran, Carla Terboven, Mark Tropin, Anastasiia Tsymbal, Katharina Ueltzen, Pablo Andres Unzueta, Archit Vasan, Tirtha Vinchurkar, Trung Vo, Gabriel Vogel, Christoph Völker, Jan Weinreich, Faradawn Yang, Mohd Zaki, Chi Zhang, Sylvester Zhang, Weijie Zhang, Ruijie Zhu, Shang Zhu, Jan Janssen, Calvin Li, Ian Foster, Ben Blaiszik

Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hybrid locations, resulting in 34 team submissions.

Language Modeling Language Modelling +2

Contrastive learning of cell state dynamics in response to perturbations

2 code implementations15 Oct 2024 Soorya Pradeep, Alishba Imran, Ziwen Liu, Taylla Milena Theodoro, Eduardo Hirata-Miyasaki, Ivan Ivanov, Madhura Bhave, Sudip Khadka, Hunter Woosley, Carolina Arias, Shalin B. Mehta

We illustrate the features and applications of DynaCLR with the following experiments: analyzing the kinetics of viral infection in human cells, detecting transient changes in cell morphology due to cell division, and mapping the dynamics of organelles due to viral infection.

Cell Tracking Contrastive Learning

Open Arms: Open-Source Arms, Hands & Control

no code implementations20 May 2022 David Hanson, Alishba Imran, Gerardo Morales, Vytas Krisciunas, Aditya Sagi, Aman Malali, Rushali Mohbe, Raviteja Upadrashta

Open Arms is a novel open-source platform of realistic human-like robotic hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the capabilities and accessibility of humanoid robotic grasping and manipulation.

Robotic Grasping

Design of an Affordable Prosthetic Arm Equipped with Deep Learning Vision-Based Manipulation

no code implementations3 Mar 2021 Alishba Imran, William Escobar, Freidoon Barez

This paper lays the complete outline of the design process of an affordable and easily accessible novel prosthetic arm that reduces the cost of prosthetics from $10, 000 to $700 on average.

A Neuro-Symbolic Humanlike Arm Controller for Sophia the Robot

no code implementations27 Oct 2020 David Hanson, Alishba Imran, Abhinandan Vellanki, Sanjeew Kanagaraj

We outline the design and construction of novel robotic arms using machine perception, convolutional neural networks, and symbolic AI for logical control and affordance indexing.

Unity

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