45 citations · 129 across the 21 of their papers we have counts for
4 papers · 1 filter
Plug & Play Directed Evolution of Proteins with Gradient-based Discrete MCMC
Patrick Emami, Aidan Perreault, Jeffrey Law +2
A long-standing goal of machine-learning-based protein engineering is to accelerate the discovery of novel mutations that improve the function of a known protein. We introduce a sa…
Learning Canonical Embeddings for Unsupervised Shape Correspondence with Locally Linear Transformations
Pan He, Patrick Emami, Sanjay Ranka +1
We present a new approach to unsupervised shape correspondence learning between pairs of point clouds. We make the first attempt to adapt the classical locally linear embedding alg…
Towards Improving the Generation Quality of Autoregressive Slot VAEs
Patrick Emami, Pan He, Sanjay Ranka +1
Unconditional scene inference and generation are challenging to learn jointly with a single compositional model. Despite encouraging progress on models that extract object-centric…
Self-Supervised Robust Scene Flow Estimation via the Alignment of Probability Density Functions
Pan He, Patrick Emami, Sanjay Ranka +1
In this paper, we present a new self-supervised scene flow estimation approach for a pair of consecutive point clouds. The key idea of our approach is to represent discrete point c…