#icml2023

Anya Rossi

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PaLM-E is a generalist, embodied language model for robotics. 🤖 It solves many tasks on 𝘮𝘶𝘭𝘵𝘪𝘱𝘭𝘦 types of robots and for 𝘮𝘶𝘭𝘵𝘪𝘱𝘭𝘦 modalities, including images and neural scene representations. Hear more from researchers at #ICML2023: 📍Booth #109 ⌚10.30 HST

PaLM-E is a generalist, embodied language model for robotics. 🤖 It solves many tasks on 𝘮𝘶𝘭𝘵𝘪𝘱𝘭𝘦 types of robots and for 𝘮𝘶𝘭𝘵𝘪𝘱𝘭𝘦 modalities, including images and neural scene representations. Hear more from researchers at #ICML2023: 📍Booth #109 ⌚10.30 HST

Google DeepMind

185,398 просмотров • 3 лет назад

Excited to share our #ICML2023 paper ✨LIV✨! Extending VIP, LIV is at once a pre-training, fine-tuning, and (zero-shot!) multi-modal reward method for (real-world!) language-conditioned robotic control. Project: Code & Model: 🧵:

Excited to share our #ICML2023 paper ✨LIV✨! Extending VIP, LIV is at once a pre-training, fine-tuning, and (zero-shot!) multi-modal reward method for (real-world!) language-conditioned robotic control. Project: Code & Model: 🧵:

55,068 просмотров • 3 лет назад

In our #ICML2023 paper (led by Ghada Sokar and with Rishabh Agarwal and utku ) we highlight the prevalence of dormant neurons in deep RL, and propose a simple method to mitigate it. Quick video summary here, and more details in thread!

In our #ICML2023 paper (led by Ghada Sokar and with Rishabh Agarwal and utku ) we highlight the prevalence of dormant neurons in deep RL, and propose a simple method to mitigate it. Quick video summary here, and more details in thread!

Pablo Samuel Castro

40,603 просмотров • 3 лет назад

Presenting MonoNeRF at #ICML2023 We train a generalizable NeRF from: ✅Large-scale monocular videos instead of one scene ✅No GT camera poses.📷🚫 Without per-scene optimization, the model can do view synthesis, depth estimation, camera pose estimation.

Presenting MonoNeRF at #ICML2023 We train a generalizable NeRF from: ✅Large-scale monocular videos instead of one scene ✅No GT camera poses.📷🚫 Without per-scene optimization, the model can do view synthesis, depth estimation, camera pose estimation.

36,578 просмотров • 3 лет назад

How can we train generative models on 100 examples without pretraining on large datasets? Presenting Adaptive IMLE, which outperforms both GANs and diffusion models. Details at Work w/ Mehran Aghabozorgi and Shichong Peng. Come by our #ICML2023 poster Wed AM 1/2

How can we train generative models on 100 examples without pretraining on large datasets? Presenting Adaptive IMLE, which outperforms both GANs and diffusion models. Details at Work w/ Mehran Aghabozorgi and Shichong Peng. Come by our #ICML2023 poster Wed AM 1/2

15,387 просмотров • 3 лет назад

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