Adaptive Categorical Discretization for Autoregressive Models
Colin Li, Ajay Jain, Pieter Abbeel
UAI 2022 Conference on Uncertainty in Artificial Intelligence
AdaCat improves the expressiveness of autoregressive models by allowing discrete density estimators to capture fine-grained variation in continuous distributions.
Zero-Shot Text-Guided Object Generation with Dream Fields
Ajay Jain, Ben Mildenhall, Jon Barron, Pieter Abbeel, Ben Poole
CVPR 2022 Conference on Computer Vision and Pattern Recognition
We combine neural rendering with multi-modal image and text representations to synthesize diverse 3D objects solely from natural language descriptions.
Contrastive Code Representation Learning
Paras Jain*, Ajay Jain*, Tianjun Zhang, Pieter Abbeel, Joseph E. Gonzalez, Ion Stoica
EMNLP 2021 Empirical Methods in Natural Language Processing
Learn to represent software functionality for automated software engineering tasks like type inference, clone detection and summarization. Improving robustness of ML4Code.
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis
Ajay Jain, Matthew Tancik, Pieter Abbeel
ICCV 2021 International Conference on Computer Vision
CLIP + NeRF: Given only a few images of an object or scene, we reconstruct its 3D structure & render novel views using prior knowledge contained in large image encoders.
Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, Pieter Abbeel
NeurIPS 2020 34th Conference on Neural Information Processing Systems
High-quality likelihood-based image generation; connect diffusion models to denoising score matching and Langevin dynamics; compression, reconstruction and interpolation
Sparse Graphical Memory for Robust Planning
Scott Emmons*, Ajay Jain*, Michael Laskin*, Thanard Kurutach, Pieter Abbeel, Deepak Pathak
NeurIPS 2020 34th Conference on Neural Information Processing Systems
Provably robust+efficient long-horizon monocular navigation combining sparse graph planning and RL. Propose two-way consistency to find landmark memories and create a topological map.
Locally Masked Convolution for Autoregressive Models
Ajay Jain, Pieter Abbeel, Deepak Pathak
UAI 2020 36th Conference on Uncertainty in AI
Efficent op allows PixelCNNs to generate images in arbitrary orders
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization
Paras Jain*, Ajay Jain*, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph E. Gonzalez
MLSys 2020 3rd Conference on Machine Learning and Systems
Use up to 5x less memory when training DNNs by recomputing activations
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Ajay Jain*, Sergio Casas Romero*, Renjie Liao*, Yuwen Xiong*, Song Feng, Sean Segal, Raquel Urtasun
CoRL 2019 3rd Conference on Robot Learning, Spotlight talk
Multimodal, long-range behavior forecasts by predicting state marginals
Revec: Program Rejuvenation through Revectorization
Charith Mendis*, Ajay Jain*, Paras Jain, Saman Amarasinghe
CC 2019 28th International Conference on Compiler Construction
Achieve performance portability for hand-vectorized programs, with up to 1.88x speedup
Autonomy for Surface Ship Interception
C. Mirabito, D.N. Subramani, T. Lolla, J. P.J. Haley, A. Jain, P.F.J. Lermusiaux, C. Li, D. Yue, Y. Liu, F. Hover, N. Pulsone, J. Edwards, K. Railey, and G. Shaw
OCEANS 2017 60th OCEANS Conference, MTS/IEEE Aberdeen
OCEANS 2017 60th OCEANS Conference, MTS/IEEE Aberdeen
Time-optimal path planning for underwater robots
