activity
20202022
most citedKohn-Sham equations as regularizer: building prior knowledge into machine-learned physics

180 citations · 234 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2022★ 18 cited

DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning

Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi +8

Continual learning aims to enable a single model to learn a sequence of tasks without catastrophic forgetting. Top-performing methods usually require a rehearsal buffer to store pa…

cs.LG2021★ 5 cited

Learning to Prompt for Continual Learning

Zifeng Wang, Zizhao Zhang, Chen-Yu Lee +7

The mainstream paradigm behind continual learning has been to adapt the model parameters to non-stationary data distributions, where catastrophic forgetting is the central challeng…

cs.CR2021

Visualization and Attack Prevention for a Sensor-Based Agricultural Monitoring System

Yifan Zhou, Zhendong Shi, Ruoxi Sun

This project proposes a sensor-based visual agricultural monitoring system. Distinguished from traditional agricultural monitoring systems, this system further analyzes basic agric…

cs.LG2020★ 2 cited

Reverse engineering learned optimizers reveals known and novel mechanisms

Niru Maheswaranathan, David Sussillo, Luke Metz +2

Learned optimizers are algorithms that can themselves be trained to solve optimization problems. In contrast to baseline optimizers (such as momentum or Adam) that use simple updat…

physics.comp-ph2020★ 180 cited

Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics

Li Li, Stephan Hoyer, Ryan Pederson +4

Including prior knowledge is important for effective machine learning models in physics, and is usually achieved by explicitly adding loss terms or constraints on model architectur…

physics.chem-ph2020★ 15 cited

Energy-based View of Retrosynthesis

Ruoxi Sun, Hanjun Dai, Li Li +2

Retrosynthesis -- the process of identifying a set of reactants to synthesize a target molecule -- is of vital importance to material design and drug discovery. Existing machine le…

cs.LG2020★ 14 cited

Using a thousand optimization tasks to learn hyperparameter search strategies

Luke Metz, Niru Maheswaranathan, Ruoxi Sun +3

We present TaskSet, a dataset of tasks for use in training and evaluating optimizers. TaskSet is unique in its size and diversity, containing over a thousand tasks ranging from ima…