8 citations · 19 across the 21 of their papers we have counts for
7 papers · 1 filter
Towards End-to-End Structure Solutions from Information-Compromised Diffraction Data via Generative Deep Learning
Gabe Guo, Judah Goldfeder, Ling Lan +5
The revolution in materials in the past century was built on a knowledge of the atomic arrangements and the structure-property relationship. The sine qua non for obtaining quantita…
Balanced and Deterministic Weight-sharing Helps Network Performance
Oscar Chang, Hod Lipson
Weight-sharing plays a significant role in the success of many deep neural networks, by increasing memory efficiency and incorporating useful inductive priors about the problem int…
Accelerating Meta-Learning by Sharing Gradients
Oscar Chang, Hod Lipson
The success of gradient-based meta-learning is primarily attributed to its ability to leverage related tasks to learn task-invariant information. However, the absence of interactio…
Teaching Robots to Build Simulations of Themselves
Yuhang Hu, Jiong Lin, Hod Lipson
The emergence of vision catalysed a pivotal evolutionary advancement, enabling organisms not only to perceive but also to interact intelligently with their environment. This transf…
Knolling bot 2.0: Enhancing Object Organization with Self-supervised Graspability Estimation
Yuhang Hu, Zhizhuo Zhang, Hod Lipson
Building on recent advancements in transformer based approaches for domestic robots performing knolling, the art of organizing scattered items into neat arrangements. This paper in…
Knolling Bot: Teaching Robots the Human Notion of Tidiness
Yuhang Hu, Judah Goldfeder, Zhizhuo Zhang +5
For robots to truly collaborate and assist humans, they must understand not only logic and instructions, but also the subtle emotions, aesthetics, and feelings that define our huma…
High-Degrees-of-Freedom Dynamic Neural Fields for Robot Self-Modeling and Motion Planning
Lennart Schulze, Hod Lipson
A robot self-model is a task-agnostic representation of the robot's physical morphology that can be used for motion planning tasks in the absence of a classical geometric kinematic…