Using geometry to choose embeddings
2025-11-11 — Empirical evaluation of local geometry in vector embeddings across models and corpora.
Tags
- machine-learning 5
- optimization 3
- bayesian 2
- noise 2
- z3 2
- time-series 1
- gaussian-processes 1
- outliers 1
- anomaly-detection 1
- python 1
- calibration 1
- simulation 1
- decision-making 1
- uncertainty 1
- information 1
- data-privacy 1
- model-equivalence 1
- operations 1
- embeddings 1
- rag 1
machine-learning
Model Equivalence using Z3
2025-11-07 — Using Z3 to prove two ML models are logically equivalent — or extract the exact counterexample where they diverge.
Noise, Stability, and Calibration
2021-05-01 — How models behave when data gets messy
Subsampling as a strategy to find optimal parameters (2/2)
2021-03-22 — Probing and fusing parameter space explorations
Subsampling as a strategy to find optimal parameters (1/2)
2021-02-14 — Using smaller samples to find optimal parameters for machine learning models
optimization
Model Equivalence using Z3
2025-11-07 — Using Z3 to prove two ML models are logically equivalent — or extract the exact counterexample where they diverge.
Subsampling as a strategy to find optimal parameters (2/2)
2021-03-22 — Probing and fusing parameter space explorations
Subsampling as a strategy to find optimal parameters (1/2)
2021-02-14 — Using smaller samples to find optimal parameters for machine learning models
bayesian
Model based simulations
2023-06-09 — Bayesian decision making applied to sales opportunities
Identifying outliers in time series
2021-02-20 — Observing the impact of outliers in small time series using gaussian processes
noise
Quantifying Information Loss
2025-10-28 — A quick experiment linking Laplace noise and data resolution, showing how privacy and precision trade off
Noise, Stability, and Calibration
2021-05-01 — How models behave when data gets messy
z3
Using geometry to choose embeddings
2025-11-11 — Empirical evaluation of local geometry in vector embeddings across models and corpora.
Model Equivalence using Z3
2025-11-07 — Using Z3 to prove two ML models are logically equivalent — or extract the exact counterexample where they diverge.
time-series
Identifying outliers in time series
2021-02-20 — Observing the impact of outliers in small time series using gaussian processes
gaussian-processes
Identifying outliers in time series
2021-02-20 — Observing the impact of outliers in small time series using gaussian processes
outliers
Identifying outliers in time series
2021-02-20 — Observing the impact of outliers in small time series using gaussian processes
anomaly-detection
Identifying outliers in time series
2021-02-20 — Observing the impact of outliers in small time series using gaussian processes
python
Extending python with Go
2021-04-03 — A simple example of how GoPy can be used to extend python with Go native code
calibration
Noise, Stability, and Calibration
2021-05-01 — How models behave when data gets messy
simulation
Model based simulations
2023-06-09 — Bayesian decision making applied to sales opportunities
decision-making
Model based simulations
2023-06-09 — Bayesian decision making applied to sales opportunities
uncertainty
Model based simulations
2023-06-09 — Bayesian decision making applied to sales opportunities
information
Quantifying Information Loss
2025-10-28 — A quick experiment linking Laplace noise and data resolution, showing how privacy and precision trade off
data-privacy
Quantifying Information Loss
2025-10-28 — A quick experiment linking Laplace noise and data resolution, showing how privacy and precision trade off
model-equivalence
Model Equivalence using Z3
2025-11-07 — Using Z3 to prove two ML models are logically equivalent — or extract the exact counterexample where they diverge.
operations
Model Equivalence using Z3
2025-11-07 — Using Z3 to prove two ML models are logically equivalent — or extract the exact counterexample where they diverge.
embeddings
Using geometry to choose embeddings
2025-11-11 — Empirical evaluation of local geometry in vector embeddings across models and corpora.
rag
Using geometry to choose embeddings
2025-11-11 — Empirical evaluation of local geometry in vector embeddings across models and corpora.