849 citations · 2k across the 67 of their papers we have counts for
6 papers · 1 filter
ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
Sungduk Yu, Zeyuan Hu, Akshay Subramaniam +44
Modern climate projections lack adequate spatial and temporal resolution due to computational constraints, leading to inaccuracies in representing critical processes like thunderst…
SURFSUP: Learning Fluid Simulation for Novel Surfaces
Arjun Mani, Ishaan Preetam Chandratreya, Elliot Creager +2
Modeling the mechanics of fluid in complex scenes is vital to applications in design, graphics, and robotics. Learning-based methods provide fast and differentiable fluid simulator…
Private Multiparty Perception for Navigation
Hui Lu, Mia Chiquier, Carl Vondrick
We introduce a framework for navigating through cluttered environments by connecting multiple cameras together while simultaneously preserving privacy. Occlusions and obstacles in…
Representing Spatial Trajectories as Distributions
Dídac Surís, Carl Vondrick
We introduce a representation learning framework for spatial trajectories. We represent partial observations of trajectories as probability distributions in a learned latent space,…
Forget-me-not! Contrastive Critics for Mitigating Posterior Collapse
Sachit Menon, David Blei, Carl Vondrick
Variational autoencoders (VAEs) suffer from posterior collapse, where the powerful neural networks used for modeling and inference optimize the objective without meaningfully using…
Metric Learning for Adversarial Robustness
Chengzhi Mao, Ziyuan Zhong, Junfeng Yang +2
Deep networks are well-known to be fragile to adversarial attacks. We conduct an empirical analysis of deep representations under the state-of-the-art attack method called PGD, and…