A woman using a drill press to manufacture brackets. The drill press bears the manufacturer label of the Chas. G. Allen Company. Companion image to ID no. 280.
Created:
1953
Contributed By:
University of Minnesota Libraries, Charles Babbage Institute.
Factory scene showing several men operating punch presses. The images is visually dynamic, with strong diagonal lines created by the position of the machinery and operators.
Created:
1948
Contributed By:
University of Minnesota Libraries, Charles Babbage Institute.
Three women using drill presses to manufacture parts. Two drill presses bear the manufacturer label of the Chas. G. Allen Company. Companion image to ID no. 283.
Created:
1953
Contributed By:
University of Minnesota Libraries, Charles Babbage Institute.
A long row of men working with drill press machinery which are driven by belts and wheels hanging from the ceiling of the factory. Two men are standing behind the row of workers, against the windows.
Created:
1915?
Contributed By:
University of Minnesota Libraries, Charles Babbage Institute.
The Madhupur Gate area of Ahmedabad is noted for the block printed textiles produced for villagers. When shopping in this area in 2014 however it was quickly apparent all the merchandise these days is mill produced and printed synthetic cloth of which this is an example. The designs and motifs however do continue the earlier block printing. One ...
Thomas Sadler Roberts gave a series of talks and lectures on dairy farms in 1903-1904. This negatives was likely produced to create a lantern slide to illustrate his lecture.
Creator:
Bell Museum of Natural History
Created:
1903
Contributed By:
University of Minnesota Libraries, University Archives.
We present an overview of how SageMath and Macaulay2 have provided crucial computational help and insight to problems in string theory over the last decade. As concrete examples, we will use the Calabi-Yau landscape. In parallel, we propose a paradigm to machine-learn the ever-expanding databases which have emerged in mathematical physics, algeb...
Creator:
He, Yang-Hui (University of London)
Created:
2019-07-23
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
We present machine learning (ML) approaches for approximately solving optimal transport problems in the high-dimensional setting. Problems of this kind frequently arise in statistics, Bayesian inference, and generative modeling, yet progress has been limited due to the curse-of-dimensionality. As our learning framework tackles the optimal cont...
Creator:
Ruthotto, Lars (Emory University)
Created:
2021-04-20
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Traffic anomalies in communication networks greatly degrade network performance. In this talk, I will survey statistical and machine learning techniques that are used to classify and detect network anomalies such as Internet worms that affect performance of routing protocols. Various classification features are used to design anomaly detection m...
Creator:
Trajkovic, Ljiljana (Simon Fraser University)
Created:
2012-09-05
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Mean-field games (MFG) is a framework to model and analyze huge populations of interacting agents that play non-cooperative differential games with applications in crowd motion, economics, finance, etc. Additionally, the PDE that arise in MFG have a rich mathematical structure and include those that appear in optimal transportation and density f...
Creator:
Nurbekyan, Levon (University of California, Los Angeles)
Created:
2020-11-03
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
We consider the problem of learning models of scattering that decomposes scene returns into a set of scattering centers with limited persistence by utilizing sparsity of scattering coefficients. We consider both mono-static and bi-static radar collection geometries along wide-angle trajectories. The resulting sparse model can be interrogated at ...
Creator:
Bouman, Charles (Purdue University)
Created:
2018-10-23
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Computer vision and image analysis are major application examples of deep learning. While computer vision and image analysis deal with existing images and produce features of these images (images to features), tomographic imaging produces images of multi-dimensional structures from experimentally measured “encoded” data as various tomographic fe...
Creator:
Wang, Ge (Rensselaer Polytechnic Institute)
Created:
2019-10-16
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
We can improve the detection of targets and anomalies in a cluttered background by more effectively estimating that background. With a good estimate of what the target-free radiance or reflectance ought to be at a pixel, we have a point of comparison with what the measured value of that pixel actually happens to be. It is common to make this est...
Creator:
Theiler, James (Los Alamos National Laboratory)
Created:
2018-10-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
