Search Results for author: Christian Borgs

Found 15 papers, 6 papers with code

A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics

no code implementations26 Jan 2024 Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Vignesh Bhethanabotla, Nakul Rampal, Omar Yaghi, Christian Borgs, Anima Anandkumar, Hongyu Guo, Jennifer Chayes

We show the efficiency and effectiveness of NeuralMD, with a 2000$\times$ speedup over standard numerical MD simulation and outperforming all other ML approaches by up to 80% under the stability metric.

Drug Discovery

Image and Data Mining in Reticular Chemistry Using GPT-4V

no code implementations9 Dec 2023 Zhiling Zheng, Zhiguo He, Omar Khattab, Nakul Rampal, Matei A. Zaharia, Christian Borgs, Jennifer T. Chayes, Omar M. Yaghi

The integration of artificial intelligence into scientific research has reached a new pinnacle with GPT-4V, a large language model featuring enhanced vision capabilities, accessible through ChatGPT or an API.

Language Modelling Large Language Model +1

ChatGPT Chemistry Assistant for Text Mining and Prediction of MOF Synthesis

1 code implementation20 Jun 2023 Zhiling Zheng, Oufan Zhang, Christian Borgs, Jennifer T. Chayes, Omar M. Yaghi

We use prompt engineering to guide ChatGPT in the automation of text mining of metal-organic frameworks (MOFs) synthesis conditions from diverse formats and styles of the scientific literature.

Chatbot Prompt Engineering

A GPT-4 Reticular Chemist for Guiding MOF Discovery

1 code implementation20 Jun 2023 Zhiling Zheng, Zichao Rong, Nakul Rampal, Christian Borgs, Jennifer T. Chayes, Omar M. Yaghi

We present a new framework integrating the AI model GPT-4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher.

In-Context Learning

Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials

1 code implementation NeurIPS 2023 Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, ZhiMing Ma, Omar Yaghi, Anima Anandkumar, Christian Borgs, Jennifer Chayes, Hongyu Guo, Jian Tang

Artificial intelligence for scientific discovery has recently generated significant interest within the machine learning and scientific communities, particularly in the domains of chemistry, biology, and material discovery.


Disincentivizing Polarization in Social Networks

no code implementations23 May 2023 Christian Borgs, Jennifer Chayes, Christian Ikeokwu, Ellen Vitercik

We present a model for content curation and personalization that avoids filter bubbles, along with algorithmic guarantees and nearly matching lower bounds.

Strategic Ranking

no code implementations16 Sep 2021 Lydia T. Liu, Nikhil Garg, Christian Borgs

Strategic classification studies the design of a classifier robust to the manipulation of input by strategic individuals.

What's in a Name? Reducing Bias in Bios without Access to Protected Attributes

no code implementations NAACL 2019 Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai

In the context of mitigating bias in occupation classification, we propose a method for discouraging correlation between the predicted probability of an individual's true occupation and a word embedding of their name.

Word Embeddings

Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting

4 code implementations27 Jan 2019 Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai

We present a large-scale study of gender bias in occupation classification, a task where the use of machine learning may lead to negative outcomes on peoples' lives.

Classification General Classification

Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation

no code implementations NeurIPS 2017 Christian Borgs, Jennifer Chayes, Christina E. Lee, Devavrat Shah

We show that the mean squared error (MSE) of our estimator converges to $0$ at the rate of $O(d^2 (pn)^{-2/5})$ as long as $\omega(d^5 n)$ random entries from a total of $n^2$ entries of $Y$ are observed (uniformly sampled), $\E[Y]$ has rank $d$, and the entries of $Y$ have bounded support.

Collaborative Filtering Community Detection +3

Entropy-SGD: Biasing Gradient Descent Into Wide Valleys

2 code implementations6 Nov 2016 Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann Lecun, Carlo Baldassi, Christian Borgs, Jennifer Chayes, Levent Sagun, Riccardo Zecchina

This paper proposes a new optimization algorithm called Entropy-SGD for training deep neural networks that is motivated by the local geometry of the energy landscape.

Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes

no code implementations20 May 2016 Carlo Baldassi, Christian Borgs, Jennifer Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina

We define a novel measure, which we call the "robust ensemble" (RE), which suppresses trapping by isolated configurations and amplifies the role of these dense regions.

Discovering Neuronal Cell Types and Their Gene Expression Profiles Using a Spatial Point Process Mixture Model

no code implementations4 Feb 2016 Furong Huang, Animashree Anandkumar, Christian Borgs, Jennifer Chayes, Ernest Fraenkel, Michael Hawrylycz, Ed Lein, Alessandro Ingrosso, Srinivas Turaga

Single-cell RNA sequencing can now be used to measure the gene expression profiles of individual neurons and to categorize neurons based on their gene expression profiles.

Maximizing Social Influence in Nearly Optimal Time

1 code implementation4 Dec 2012 Christian Borgs, Michael Brautbar, Jennifer Chayes, Brendan Lucier

Finally, we show that this runtime is optimal (up to logarithmic factors) for any beta and fixed seed size k.

Data Structures and Algorithms Social and Information Networks Physics and Society F.2.2; J.4

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