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Improving predictability of cell culture processes during biologics manufacturing scale-up through hybrid modeling
(Massachusetts Institute of Technology, 2020)
In the biotechnology industry, commercial manufacturing of biologic drugs occurs in large-scale production bioreactors (15,000L), but process development occurs in lab-scale production bioreactors (2-3L). Cell culture ...
High-fidelity inversion at low-photon counts using deep learning and random phase modulation
(Massachusetts Institute of Technology, 2020)
Often objects are highly transparent or pure phase with no absorption of ambient light; phase information of the objects conveys most of the knowledge on their appearance. Phase is generally retrieved from raw intensity, ...
Very-large-scale-integration of complementary carbon nanotube field-effect transistors
(Massachusetts Institute of Technology, 2020)
Electronics is approaching a major paradigm shift as silicon transistor scaling no longer yields historical energy-efficiency benefits, spurring research towards beyond-silicon nanotechnologies. In particular, carbon ...
Mixed-precision NN accelerator with neural-hardware architecture search
(Massachusetts Institute of Technology, 2020)
Neural architecture and hardware architecture co-design is an effective way to enable specialization and acceleration for deep neural networks (DNNs). The design space and its exploration methodology impact efficiency and ...
Hardware-efficient deep learning for 3D point cloud
(Massachusetts Institute of Technology, 2020)
3D neural networks are widely used in real-world applications (e.g., AR/VR headsets, self-driving cars). They are required to be fast and accurate; however, limited hardware resources on edge devices make these requirements ...
Auctions of digital goods with externalities
(Massachusetts Institute of Technology, 2020)
Data is increasingly important for firms, regulators, and researchers to develop accurate models for decision-making. Since data sets often need to be externally acquired, a systematic way to value and trade data is ...
Quantum efficiency of Josephson traveling wave parametric amplifiers with many-Mode processes
(Massachusetts Institute of Technology, 2020)
Josephson traveling wave parametric amplifiers (JTWPAs) are widely used in superconducting qubit and microwave quantum optics experiments. Compared with cavity-based Josephson parametric amplifiers (JPAs), JTWPAs have ~10dB ...
Wasserstein barycenters : statistics and optimization
(Massachusetts Institute of Technology, 2020)
We study a geometric notion of average, the barycenter, over 2-Wasserstein space. We significantly advance the state of the art by introducing extendible geodesics, a simple synthetic geometric condition which implies ...
Explainable AI foundations to support human-robot teaching and learning
(Massachusetts Institute of Technology, 2020)
In human-to-human communication, the dual interactions of teaching and learning are indispensable to knowledge transfer. Explanations are core to these interactions: in humans, explanations support model comparison and ...
Statistical and computational methods for analysis of spatial transcriptomics data
(Massachusetts Institute of Technology, 2020)
Spatial transcriptomic technologies measure gene expression at increasing spatial resolution, approaching individual cells. One limitation of current technologies is that spatial measurements may contain contributions from ...