50 citations · 155 across the 10 of their papers we have counts for
10 papers
Robot-Assisted Drilling on Curved Surfaces with Haptic Guidance under Adaptive Admittance Control
Alireza Madani, Pouya P. Niaz, Berk Guler +2
Drilling a hole on a curved surface with a desired angle is prone to failure when done manually, due to the difficulties in drill alignment and also inherent instabilities of the t…
ProGen2: Exploring the Boundaries of Protein Language Models
Erik Nijkamp, Jeffrey Ruffolo, Eli N. Weinstein +2
Attention-based models trained on protein sequences have demonstrated incredible success at classification and generation tasks relevant for artificial intelligence-driven protein…
An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning
Berk Guler, Pouya P. Niaz, Alireza Madani +2
In this paper, we propose a supervised learning approach based on an Artificial Neural Network (ANN) model for real-time classification of subtasks in a physical human-robot intera…
Deep Extrapolation for Attribute-Enhanced Generation
Alvin Chan, Ali Madani, Ben Krause +1
Attribute extrapolation in sample generation is challenging for deep neural networks operating beyond the training distribution. We formulate a new task for extrapolation in sequen…
Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models
Pascal Sturmfels, Jesse Vig, Ali Madani +1
For protein sequence datasets, unlabeled data has greatly outpaced labeled data due to the high cost of wet-lab characterization. Recent deep-learning approaches to protein predict…
BERTology Meets Biology: Interpreting Attention in Protein Language Models
Jesse Vig, Ali Madani, Lav R. Varshney +3
Transformer architectures have proven to learn useful representations for protein classification and generation tasks. However, these representations present challenges in interpre…
ProGen: Language Modeling for Protein Generation
Ali Madani, Bryan McCann, Nikhil Naik +5
Generative modeling for protein engineering is key to solving fundamental problems in synthetic biology, medicine, and material science. We pose protein engineering as an unsupervi…
ProDyn0: Inferring calponin homology domain stretching behavior using graph neural networks
Ali Madani, Cyna Shirazinejad, Jia Rui Ong +2
Graph neural networks are a quickly emerging field for non-Euclidean data that leverage the inherent graphical structure to predict node, edge, and global-level properties of a sys…
Bimodal network architectures for automatic generation of image annotation from text
Mehdi Moradi, Ali Madani, Yaniv Gur +2
Medical image analysis practitioners have embraced big data methodologies. This has created a need for large annotated datasets. The source of big data is typically large image col…
Fast and accurate classification of echocardiograms using deep learning
Ali Madani, Ramy Arnaout, Mohammad Mofrad +1
Echocardiography is essential to modern cardiology. However, human interpretation limits high throughput analysis, limiting echocardiography from reaching its full clinical and res…