activity
20162022
most citedDiffTaichi: Differentiable Programming for Physical Simulation

75 citations · 133 across the 6 of their papers we have counts for

collaborators

8 papers

cs.PL20222 cited

Formal Semantics for the Halide Language

Alex Reinking, Gilbert Louis Bernstein, Jonathan Ragan-Kelley

We present the first formalization and metatheory of language soundness for a user-schedulable language, the widely used array processing language Halide. User-schedulable language…

cs.GR202217 cited

Designing Perceptual Puzzles by Differentiating Probabilistic Programs

Kartik Chandra, Tzu-Mao Li, Joshua Tenenbaum +1

We design new visual illusions by finding "adversarial examples" for principled models of human perception -- specifically, for probabilistic models, which treat vision as Bayesian…

cs.PL20211 cited

Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming

Adam Paszke, Daniel Johnson, David Duvenaud +5

We present a novel programming language design that attempts to combine the clarity and safety of high-level functional languages with the efficiency and parallelism of low-level n…

cs.PL20205 cited

Differentiating a Tensor Language

Gilbert Bernstein, Michael Mara, Tzu-Mao Li +2

How does one compile derivatives of tensor programs, such that the resulting code is purely functional (hence easier to optimize and parallelize) and provably efficient relative to…

cs.LG202033 cited

Neural Kernels Without Tangents

Vaishaal Shankar, Alex Fang, Wenshuo Guo +4

We investigate the connections between neural networks and simple building blocks in kernel space. In particular, using well established feature space tools such as direct sum, ave…

cs.LG201975 cited

DiffTaichi: Differentiable Programming for Physical Simulation

Yuanming Hu, Luke Anderson, Tzu-Mao Li +4

We present DiffTaichi, a new differentiable programming language tailored for building high-performance differentiable physical simulators. Based on an imperative programming langu…