A novel methodology is proposed for clustering multivariate time series data using energy distance defined in Székely and Rizzo (2013). Specifically, a dissimilarity matrix is formed using the energy distance statistic to measure separation between...
''Noisy'' datasets (regimes with low signal to noise ratios, small sample sizes, faulty data collection, etc) remain a key research frontier for classification methods with both theoretical and practical implications. We introduce FINDER, a rigorous...
Aerial imagery can be used for important work on a global scale. Nevertheless, the analysis of this data using neural network architectures lags behind the current state-of-the-art on popular datasets such as PASCAL VOC, CityScapes and Camvid. In thi...
The murder of George Floyd centered Minneapolis, Minnesota, in conversations on racial injustice in the US. We leverage open data from the Minneapolis Police Department to analyze individual, geographic, and temporal patterns in more than 170,000 pol...
Recent advances in generative modeling have enabled the generation of high-quality synthetic data that is applicable in a variety of domains, including face recognition. Here, state-of-the-art generative models typically rely on conditioning and fine...
This paper describes the submission of UZH_CLyp for the SemEval 2023 Task 9 "Multilingual Tweet Intimacy Analysis". We achieved second-best results in all 10 languages according to the official Pearson's correlation regression evaluation measure. Our...
*Premier League Fantrax Waiver Wire — Weekly Picks with Insight* ***Note: All stats mentioned are listed as values per 90 minutes played (source FotMob)*** As a bit of a data nerd, it was sad to ...
(The charts in this post were made from the 8,885 posts that were made on r-Conservative between 11/20/25 and 2/20/26. The [anonymized source data is here](https://pastebin.com/KxS57YaY).) \[edit: the...
Unmanned aerial vehicles (UAVs) are now beginning to be deployed for enhancing the network performance and coverage in wireless communication. However, due to the limitation of their on-board power and flight time, it is challenging to obtain an opti...
Within the human-robot interaction (HRI) community, many researchers have focused on the careful design of human-subjects studies. However, other parts of the community, e.g., the technical advances community, also need to do human-subjects studies t...
Boyuan Zhang The assumption of group heterogeneity has become popular in panel data models. In-stead of modeling heterogeneity via unit-specific coefficients, the cross-sectional units are as-sumed …
RESEARCH STATEMENT Boyuan Zhang University of Pennsylvania Website: boyuan-zhang.github.io such as grouped heterogeneity in panel data models and density forecast com-binations. h represent …
Reverberation Time (T60) is an important measure for characterizing the properties of a room. The author's T60 estimation algorithm was previously tested on simulated data where the noise is artificially added to the speech after convolution with a i...
Learning from demonstrations has shown to be an effective approach to robotic manipulation, especially with the recently collected large-scale robot data with teleoperation systems. Building an efficient teleoperation system across diverse robot plat...
One-neutron knockout reactions have been widely used to extract information about the single-particle structure of nuclei from the valley of stability to the driplines. The interpretation of knockout data relies on reaction models, where the uncertai...
We analyze experimental data on double diffusive convection in an electrochemical cell in the finger regime. All fingers in the experiments are bounded on at least one end by a solid wall. The properties of these fingers are compared with those of fi...
In this work, we carried out a study about the use of attention-based algorithms to automate the categorization of Brazilian case law documents. We used data from the Kollemata Project to produce two distinct datasets with adequate class systems. The...
One of the core problems in statistical models is the estimation of a posterior distribution. For topic models, the problem of posterior inference for individual texts is particularly important, especially when dealing with data streams, but is often...
This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track...
Based on NFL game data we try to predict the outcome of a play in multiple different ways. An application of this is the following: by plugging in various play options one could determine the best play for a given situation in real time. While the ou...