Harmonic Exponential Families on Manifolds
Authors: Taco Cohen, Max Welling
ICML 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental results show that harmonic densities yield a significantly higher likelihood than the best competing method, while being orders of magnitude faster to train. |
| Researcher Affiliation | Academia | Taco S. Cohen T.S.COHEN@UVA.NL University of Amsterdam Max Welling M.WELLING@UVA.NL University of Amsterdam University of California Irvine Canadian Institute for Advanced Research |
| Pseudocode | Yes | So we have an efficient algorithm for computing moments: 1. Compute ϕ = exp (F 1η). 2. Compute M = F ϕ 3. Compute Ep(g|η) [T(g)] = M/M 0 00. [...] To find the optimal transformation, first perform posterior inference (steps 1 and 2) and then maximize (step 3): 1. Compute ˆx = F x and ˆy = F y. 2. Compute ηλ = ηλ + 1 σ2 dim λ ˆxλˆy T λ 3. Compute g = arg maxi[F 1 η](gi) |
| Open Source Code | No | The paper does not provide concrete access to its own source code. |
| Open Datasets | Yes | We obtained the Significant Earthquake Dataset (NGDC, 2015) from the National Geophysical Datacenter of the National Oceanographic and Athmospheric Administration. |
| Dataset Splits | Yes | Figure 2 shows the average train and test log-likelihood over 5 cross-validation folds, for the spherical harmonic density and the mixture of Kent distribution. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running its experiments. |
| Software Dependencies | No | The paper mentions software like Python, NFFT library, SciPy routines, and L-BFGS algorithm, but does not provide specific version numbers for these dependencies. |
| Experiment Setup | No | The paper describes regularization methods and optimization algorithms, but does not provide specific concrete hyperparameter values (e.g., learning rate, batch size) or detailed training configurations for its experiments. |