User profiles for Daniel Manu
Daniel Manu, Ph.D.AI/ML Scientist Verified email at unm.edu Cited by 82 |
[HTML][HTML] Seismic waveform inversion capability on resource-constrained edge devices
Seismic full wave inversion (FWI) is a widely used non-linear seismic imaging method used
to reconstruct subsurface velocity images, however it is time consuming, has high …
to reconstruct subsurface velocity images, however it is time consuming, has high …
GraphGANFed: A federated generative framework for graph-structured molecules towards efficient drug discovery
Recent advances in deep learning have accelerated its use in various applications, such as
cellular image analysis and molecular discovery. In molecular discovery, a generative …
cellular image analysis and molecular discovery. In molecular discovery, a generative …
Fl-disco: Federated generative adversarial network for graph-based molecule drug discovery: Special session paper
The outbreak of the global COVID-19 pandemic emphasizes the importance of collaborative
drug discovery for high effectiveness; however, due to the stringent data regulation, data …
drug discovery for high effectiveness; however, due to the stringent data regulation, data …
Enhancing IoT Security with Asynchronous Federated Learning for Seismic Inversion
Seismic data/images are critical to understand the structure of subsurfaces. However, for
accurate structural analysis, seismic images need to be converted into velocity images that can …
accurate structural analysis, seismic images need to be converted into velocity images that can …
AsyncFedGAN: An Efficient and Staleness-aware Asynchronous Federated Learning Framework for Generative Adversarial Networks
Generative Adversarial Networks (GANs) are deep learning models that learn and generate
new samples similar to existing ones. Traditionally, GANs are trained in centralized data …
new samples similar to existing ones. Traditionally, GANs are trained in centralized data …
Co-exploration of graph neural network and network-on-chip design using automl
Recently, Graph Neural Networks (GNNs) have exhibited high efficiency in several graph-based
machine learning tasks. Compared with the neural networks for computer vision or …
machine learning tasks. Compared with the neural networks for computer vision or …
Ground-based communication support for air corridors
Advanced Air Mobility (AAM) is envisioned to bring a new mode of air transportation with
promising benefits to the society, at large. AAM services such as air taxis and air ambulances …
promising benefits to the society, at large. AAM services such as air taxis and air ambulances …
Deep Learning Framework for Graph-Based Molecular Drug Discovery
D Manu - 2024 - search.proquest.com
Daniel Manu Candidate Electrical and Computer Engineering Department This dissertation
is approved, and it is acceptable in qual Page 1 Daniel Manu Candidate Electrical and …
is approved, and it is acceptable in qual Page 1 Daniel Manu Candidate Electrical and …
HMC-TRAN A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU
Although Transformer-based deep learning models have been widely used in many natural
language processing (NLP) tasks as well as computer vision, they suffer from gigantic model …
language processing (NLP) tasks as well as computer vision, they suffer from gigantic model …
An Integrated Hardware-Software System to Identify the Underlying Distribution of PD Pulse Height Records
In this paper, we have incorporated a software capability to extend the PDPAS developed in
[11] where the incoming PD pulses are classified into PD pulse height distributions whilst …
[11] where the incoming PD pulses are classified into PD pulse height distributions whilst …