Search Results for author:
Found 5 papers, 1 papers with code
TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training
By stacking training optimizations, we demonstrate accelerations of 65. 08% with 1D parallelism at the 128-GPU scale (Llama 3. 1 8B), an additional 12. 59% with 2D parallelism at the 256-GPU scale (Llama 3. 1 70B), and an additional 30% with 3D parallelism at the 512-GPU scale (Llama 3. 1 405B) on NVIDIA H100 GPUs over optimized baselines.
Domain Adaptation of Networks for Camera Pose Estimation: Learning Camera Pose Estimation Without Pose Labels
One of the key criticisms of deep learning is that large amounts of expensive and difficult-to-acquire training data are required in order to train models with high performance and good generalization capabilities.
Experimental Study on Probabilistic ToA and AoA Joint Localization in Real Indoor Environments
In this paper, we study probabilistic time-of-arrival (ToA) and angle-of-arrival (AoA) joint localization in real indoor environments.
Networking and Internet Architecture Signal Processing
CSI-Based Multi-Antenna and Multi-Point Indoor Positioning Using Probability Fusion
Channel state information (CSI)-based fingerprinting via neural networks (NNs) is a promising approach to enable accurate indoor and outdoor positioning of user equipments (UEs), even under challenging propagation conditions.
Probabilistic Time of Arrival Localization
In this paper, we take a new approach for time of arrival geo-localization.
