Using and Abusing Equivariance: Investigating Differences between Exact and Approximate Equivariance in Computer Vision

In this work we show how Group Equivariant Convolutional Neural Networks use subsampling to learn to break equivariance to their symmetries. We focus on the 2D roto-translation group and investigate the impact of broken equivariance on network performance. We show that changing the input dimension of a network by as little as a single pixel can...

Charge-Sampling DTC based Fractional-N Phase-Locked Loop with Background DTC Gain Calibration

Phase-locked loops (PLLs) are ubiquitous in many RF applications such as frequency synthesizers in wireline and wireless transceivers. In this project, a charge-sampling PLL has been designed, which employs a charge-domain sub-sampling phase detector. The high gain of the phase detector helps suppress the in-band phase noise, while the lowered...

Mobilizing Young Researchers, Citizen Scientists, and Mobile Technology to Close Water Data Gaps: Methods Development and Initial Results in the Kathmandu Valley, Nepal

Data gaps as educational opportunities - mobilizing young researchers, citizen scientists, and mobile technology in data and resource scarce areas. This dissertation chronicles these themes through the lessons learned along the fledgling journey of SmartPhones4Water (S4W) and S4W-Nepal, from inception through the first few years of...

Continuity vs. the Crowd—Tradeoffs Between Continuous and Intermittent Citizen Hydrology Streamflow Observations

Hydrologic data has traditionally been collected with permanent installations of sophisticated and accurate but expensive monitoring equipment at limited numbers of sites. Consequently, observation frequency and costs are high, but spatial coverage of the data is limited. Citizen Hydrology can possibly overcome these challenges by leveraging...