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20122023
most citedA Berkeley View of Systems Challenges for AI

176 citations · 564 across the 35 of their papers we have counts for

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11 papers · 1 filter

cs.LG202317 cited

Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Benyamin Ghojogh, Ali Ghodsi

This is a tutorial paper on Recurrent Neural Network (RNN), Long Short-Term Memory Network (LSTM), and their variants. We start with a dynamical system and backpropagation through…

cs.LG2022

When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation

Ehsan Kamalloo, Mehdi Rezagholizadeh, Ali Ghodsi

Data Augmentation (DA) is known to improve the generalizability of deep neural networks. Most existing DA techniques naively add a certain number of augmented samples without consi…

cs.LG202139 cited

SymbolicGPT: A Generative Transformer Model for Symbolic Regression

Mojtaba Valipour, Bowen You, Maysum Panju +1

Symbolic regression is the task of identifying a mathematical expression that best fits a provided dataset of input and output values. Due to the richness of the space of mathemati…

cs.LG20202 cited

Symbolically Solving Partial Differential Equations using Deep Learning

Maysum Panju, Kourosh Parand, Ali Ghodsi

We describe a neural-based method for generating exact or approximate solutions to differential equations in the form of mathematical expressions. Unlike other neural methods, our…

cs.LG20206 cited

A Neuro-Symbolic Method for Solving Differential and Functional Equations

Maysum Panju, Ali Ghodsi

When neural networks are used to solve differential equations, they usually produce solutions in the form of black-box functions that are not directly mathematically interpretable.…

cs.LG201915 cited

DeepNovoV2: Better de novo peptide sequencing with deep learning

Rui Qiao, Ngoc Hieu Tran, Lei Xin +3

Personalized cancer vaccines are envisioned as the next generation rational cancer immunotherapy. The key step in developing personalized therapeutic cancer vaccines is to identify…