One of the issues I discussed with students in class today is the ethical component: the Bayes nets will inherit whatever biases Jed has internalized from its training data.
Excited to share our #CoRL2026 work PhysCoRe: a physics-corrected world model for deformable objects!
We couple a physics-based simulator with two feed-forward modules: one infers material from vision, the other corrects its internal dynamics.
Check: lunarlab-gatech.github.io/Ph…
You fine-tune a robot foundation model on a hard task. It gets 25%. Now what?
Introducing Q-Planning, a learning-based harness that lets large black-box robot policies recursively self-improve.
On a hard fine-grained task: 25% → 80% in 100 robot attempts (~30 mins), no extra human data.
q-planning.github.io/
1/n 🧵
Exciting to see how the community puts @gtsam4 to work! In a guest post, Jash Shah explores an application of factor graphs to 3D Gaussian Splatting, bringing neural rendering together with pose graphs, loop closures, robust noise models, and iSAM2.
gtsam.org/2026/08/04/gaussia…#GTSAM#SLAM#3DGS
One of the worst heatwaves in European history is underway.
Peak high temperatures forecast this week:
France: 45°C / 113°F Monday-Tuesday
London: 39°C / 102°F
Amsterdam: 34°C / 93°F
Berlin: 38°C / 100°F
Paris: 41°C / 106°F
Huzzah! A new GTSAM blog post by Kosuke Inoue: RTK GNSS double-difference factors for pseudorange + carrier phase, with lever-arm variants for GNSS-IMU fusion and example results on a Tokyo urban driving dataset.
A great community contribution to GTSAM’s navigation module. Link in replies.